Type
| Topic | Name | Reference | Link |
|---|
| Code | Structure from motion | libmv | | http://code.google.com/p/libmv/ |
| Code | Dimension Reduction | LLE | | http://www.cs.nyu.edu/~roweis/lle/code.html |
| Code | Clustering | Spectral Clustering - UCSD Project | | http://vision.ucsd.edu/~sagarwal/spectral-0.2.tgz |
| Code | Clustering | K-Means - Oxford Code | | http://www.cs.ucf.edu/~vision/Code/vggkmeans.zip |
| Code | Image Deblurring | Non-blind deblurring (and blind denoising) with integrated noise estimation | U. Schmidt, K. Schelten, and S. Roth. Bayesian deblurring with integrated noise estimation, CVPR 2011 | http://www.gris.tu-darmstadt.de/research/visinf/software/index.en.htm |
| Code | Structure from motion | Structure from Motion toolbox for Matlab by Vincent Rabaud | | http://code.google.com/p/vincents-structure-from-motion-matlab-toolbox/ |
| Code | Multiple View Geometry | Matlab Functions for Multiple View Geometry | | http://www.robots.ox.ac.uk/~vgg/hzbook/code/ |
| Code | Object Detection | Max-Margin Hough Transform | S. Maji and J. Malik, Object Detection Using a Max-Margin Hough Transform. CVPR 2009 | http://www.cs.berkeley.edu/~smaji/projects/max-margin-hough/ |
| Code | Image Segmentation | SLIC Superpixels | R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk, SLIC Superpixels, EPFL Technical Report, 2010 | http://ivrg.epfl.ch/supplementary_material/RK_SLICSuperpixels/index.html |
| Code | Visual Tracking | Tracking using Pixel-Wise Posteriors | C. Bibby and I. Reid, Tracking using Pixel-Wise Posteriors, ECCV 2008 | http://www.robots.ox.ac.uk/~cbibby/research_pwp.shtml |
| Code | Visual Tracking | Visual Tracking with Histograms and Articulating Blocks | S. M. Shshed Nejhum, J. Ho, and M.-H.Yang, Visual Tracking with Histograms and Articulating Blocks, CVPR 2008 | http://www.cise.ufl.edu/~smshahed/tracking.htm |
| Code | Sparse Representation | Robust Sparse Coding for Face Recognition | M. Yang, L. Zhang, J. Yang and D. Zhang, “Robust Sparse Coding for Face Recognition,” CVPR 2011 | http://www4.comp.polyu.edu.hk/~cslzhang/code/RSC.zip |
| Code | Feature Detection andFeature Extraction | Groups of Adjacent Contour Segments | V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid, Groups of Adjacent Contour Segments for Object Detection, PAMI, 2007 | http://www.robots.ox.ac.uk/~vgg/share/ferrari/release-kas-v102.tgz |
| Code | Density Estimation | Kernel Density Estimation Toolbox | | http://www.ics.uci.edu/~ihler/code/kde.html |
| Code | Illumination, Reflectance, and Shadow | Ground shadow detection | J.-F. Lalonde, A. A. Efros, S. G. Narasimhan, Detecting Ground Shadowsin Outdoor Consumer Photographs, ECCV 2010 | http://www.jflalonde.org/software.html#shadowDetection |
| Code | Image Denoising,Image Super-resolution, andImage Deblurring | Learning Models of Natural Image Patches | D. Zoran and Y. Weiss, From Learning Models of Natural Image Patches to Whole Image Restoration, ICCV, 2011 | http://www.cs.huji.ac.il/~daniez/ |
| Code | Illumination, Reflectance, and Shadow | Estimating Natural Illumination from a Single Outdoor Image | J-F. Lalonde, A. A. Efros, S. G. Narasimhan, Estimating Natural Illumination from a Single Outdoor Image , ICCV 2009 | http://www.cs.cmu.edu/~jlalonde/software.html#skyModel |
| Code | Visual Tracking | Lucas-Kanade affine template tracking | S. Baker and I. Matthews, Lucas-Kanade 20 Years On: A Unifying Framework, IJCV 2002 | http://www.mathworks.com/matlabcentral/fileexchange/24677-lucas-kanade-affine-template-tracking |
| Code | Saliency Detection | Saliency-based video segmentation | K. Fukuchi, K. Miyazato, A. Kimura, S. Takagi and J. Yamato, Saliency-based video segmentation with graph cuts and sequentially updated priors, ICME 2009 | http://www.brl.ntt.co.jp/people/akisato/saliency3.html |
| Code | Dimension Reduction | Laplacian Eigenmaps | | http://www.cse.ohio-state.edu/~mbelkin/algorithms/Laplacian.tar |
| Code | Illumination, Reflectance, and Shadow | What Does the Sky Tell Us About the Camera? | J-F. Lalonde, S. G. Narasimhan, A. A. Efros, What Does the Sky Tell Us About the Camera?, ECCV 2008 | http://www.cs.cmu.edu/~jlalonde/software.html#skyModel |
| Code | Image Filtering | SVM for Edge-Preserving Filtering | Q. Yang, S. Wang, and N. Ahuja, SVM for Edge-Preserving Filtering, CVPR 2010 | http://vision.ai.uiuc.edu/~qyang6/publications/code/cvpr-10-svmbf/program_video_conferencing.zip |
| Code | Image Segmentation | Recovering Occlusion Boundaries from a Single Image | D. Hoiem, A. Stein, A. A. Efros, M. Hebert, Recovering Occlusion Boundaries from a Single Image, ICCV 2007. | http://www.cs.cmu.edu/~dhoiem/software/ |
| Code | Visual Tracking | Visual Tracking Decomposition | J Kwon and K. M. Lee, Visual Tracking Decomposition, CVPR 2010 | http://cv.snu.ac.kr/research/~vtd/ |
| Code | Visual Tracking | GPU Implementation of Kanade-Lucas-Tomasi Feature Tracker | S. N Sinha, J.-M. Frahm, M. Pollefeys and Y. Genc, Feature Tracking and Matching in Video Using Programmable Graphics Hardware, MVA, 2007 | http://cs.unc.edu/~ssinha/Research/GPU_KLT/ |
| Code | Object Detection | Recognition using regions | C. Gu, J. J. Lim, P. Arbelaez, and J. Malik, CVPR 2009 | http://www.cs.berkeley.edu/~chunhui/publications/cvpr09_v2.zip |
| Code | Saliency Detection | Saliency Using Natural statistics | L. Zhang, M. Tong, T. Marks, H. Shan, and G. Cottrell. Sun: A bayesian framework for saliency using natural statistics. Journal of Vision, 2008 | http://cseweb.ucsd.edu/~l6zhang/ |
| Code | Image Filtering | Local Laplacian Filters | S. Paris, S. Hasinoff, J. Kautz, Local Laplacian Filters: Edge-Aware Image Processing with a Laplacian Pyramid, SIGGRAPH 2011 | http://people.csail.mit.edu/sparis/publi/2011/siggraph/matlab_source_code.zip |
| Code | Common Visual Pattern Discovery | Sketching the Common | S. Bagon, O. Brostovsky, M. Galun and M. Irani, Detecting and Sketching the Common, CVPR 2010 | http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/SketchCommonCVPR10_v1.1.tar.gz |
| Code | Image Denoising | BLS-GSM | | http://decsai.ugr.es/~javier/denoise/ |
| Code | Camera Calibration | Epipolar Geometry Toolbox | G.L. Mariottini, D. Prattichizzo, EGT: a Toolbox for Multiple View Geometry and Visual Servoing, IEEE Robotics & Automation Magazine, 2005 | http://egt.dii.unisi.it/ |
| Code | Depth Sensor | Kinect SDK | http://www.microsoft.com/en-us/kinectforwindows/ | http://www.microsoft.com/en-us/kinectforwindows/ |
| Code | Image Super-resolution | Self-Similarities for Single Frame Super-Resolution | C.-Y. Yang, J.-B. Huang, and M.-H. Yang, Exploiting Self-Similarities for Single Frame Super-Resolution, ACCV 2010 | https://eng.ucmerced.edu/people/cyang35/ACCV10.zip |
| Code | Image Denoising | Gaussian Field of Experts | | http://www.cs.huji.ac.il/~yweiss/BRFOE.zip |
| Code | Object Detection | Poselet | L. Bourdev, J. Malik, Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations, ICCV 2009 | http://www.eecs.berkeley.edu/~lbourdev/poselets/ |
| Code | Kernels and Distances | Efficient Earth Mover's Distance with L1 Ground Distance (EMD_L1) | H. Ling and K. Okada, An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison, PAMI 2007 | http://www.dabi.temple.edu/~hbling/code/EmdL1_v3.zip |
| Code | Nearest Neighbors Matching | Spectral Hashing | Y. Weiss, A. Torralba, R. Fergus, Spectral Hashing, NIPS 2008 | http://www.cs.huji.ac.il/~yweiss/SpectralHashing/ |
| Code | Image Denoising | Field of Experts | | http://www.cs.brown.edu/~roth/research/software.html |
| Code | Image Segmentation | Multiscale Segmentation Tree | E. Akbas and N. Ahuja, “From ramp discontinuities to segmentation tree,” ACCV 2009 and N. Ahuja, “A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection,” PAMI 1996 | http://vision.ai.uiuc.edu/segmentation |
| Code | Multiple Instance Learning | MILIS | Z. Fu, A. Robles-Kelly, and J. Zhou, MILIS: Multiple instance learning with instance selection, PAMI 2010 | |
| Code | Nearest Neighbors Matching | FLANN: Fast Library for Approximate Nearest Neighbors | | http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN |
| Code | Feature Detection andFeature Extraction | Maximally stable extremal regions (MSER) - VLFeat | J. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002 | http://www.vlfeat.org/ |
| Code | Alpha Matting | Spectral Matting | A. Levin, A. Rav-Acha, D. Lischinski. Spectral Matting. PAMI 2008 | http://www.vision.huji.ac.il/SpectralMatting/ |
| Code | Multi-View Stereo | Patch-based Multi-view Stereo Software | Y. Furukawa and J. Ponce, Accurate, Dense, and Robust Multi-View Stereopsis, PAMI 2009 | http://grail.cs.washington.edu/software/pmvs/ |
| Code | Clustering | Self-Tuning Spectral Clustering | | http://www.vision.caltech.edu/lihi/Demos/SelfTuningClustering.html |
| Code | Feature Extraction andObject Detection | Histogram of Oriented Graidents - OLT for windows | N. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005 | http://www.computing.edu.au/~12482661/hog.html |
| Code | Image Understanding | Nonparametric Scene Parsing via Label Transfer | C. Liu, J. Yuen, and Antonio Torralba, Nonparametric Scene Parsing via Label Transfer, PAMI 2011 | http://people.csail.mit.edu/celiu/LabelTransfer/index.html |
| Code | Multiple Kernel Learning | DOGMA | F. Orabona, L. Jie, and B. Caputo. Online-batch strongly convex multi kernel learning. CVPR, 2010 | http://dogma.sourceforge.net/ |
| Code | Distance Metric Learning | Matlab Toolkit for Distance Metric Learning | | http://www.cs.cmu.edu/~liuy/distlearn.htm |
| Code | Optical Flow | Black and Anandan's Optical Flow | | http://www.cs.brown.edu/~dqsun/code/ba.zip |
| Code | Text Recognition | Text recognition in the wild | K. Wang, B. Babenko, and S. Belongie, End-to-end Scene Text Recognition, ICCV 2011 | http://vision.ucsd.edu/~kai/grocr/ |
| Code | MRF Optimization | MRF Minimization Evaluation | R. Szeliski et al., A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors, PAMI, 2008 | http://vision.middlebury.edu/MRF/ |
| Code | Saliency Detection | Context-aware saliency detection | S. Goferman, L. Zelnik-Manor, and A. Tal. Context-aware saliency detection. In CVPR, 2010. | http://webee.technion.ac.il/labs/cgm/Computer-Graphics-Multimedia/Software/Saliency/Saliency.html |
| Code | Saliency Detection | Learning to Predict Where Humans Look | T. Judd and K. Ehinger and F. Durand and A. Torralba, Learning to Predict Where Humans Look, ICCV, 2009 | http://people.csail.mit.edu/tjudd/WherePeopleLook/index.html |
| Code | Stereo | Stereo Evaluation | D. Scharstein and R. Szeliski. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms, IJCV 2001 | http://vision.middlebury.edu/stereo/ |
| Code | Image Segmentation | Quick-Shift | A. Vedaldi and S. Soatto, Quick Shift and Kernel Methodsfor Mode Seeking, ECCV, 2008 | http://www.vlfeat.org/overview/quickshift.html |
| Code | Saliency Detection | Graph-based visual saliency | J. Harel, C. Koch, and P. Perona. Graph-based visual saliency. NIPS, 2007 | http://www.klab.caltech.edu/~harel/share/gbvs.php |
| Code | Clustering | K-Means - VLFeat | | http://www.vlfeat.org/ |
| Code | Object Detection | A simple object detector with boosting | ICCV 2005 short courses on Recognizing and Learning Object Categories | http://people.csail.mit.edu/torralba/shortCourseRLOC/boosting/boosting.html |
| Code | Image Quality Assessment | Structural SIMilarity | | https://ece.uwaterloo.ca/~z70wang/research/ssim/ |
| Code | Structure from motion | FIT3D | | http://www.fit3d.info/ |
| Code | Image Denoising | BM3D | | http://www.cs.tut.fi/~foi/GCF-BM3D/ |
| Code | Saliency Detection | Discriminant Saliency for Visual Recognition from Cluttered Scenes | D. Gao and N. Vasconcelos, Discriminant Saliency for Visual Recognition from Cluttered Scenes, NIPS, 2004 | http://www.svcl.ucsd.edu/projects/saliency/ |
| Code | Image Denoising | Nonlocal means with cluster trees | T. Brox, O. Kleinschmidt, D. Cremers, Efficient nonlocal means for denoising of textural patterns, TIP 2008 | http://lmb.informatik.uni-freiburg.de/resources/binaries/nlmeans_brox_tip08Linux64.zip |
| Code | Saliency Detection | Global Contrast based Salient Region Detection | M.-M. Cheng, G.-X. Zhang, N. J. Mitra, X. Huang, S.-M. Hu. Global Contrast based Salient Region Detection. CVPR, 2011 | http://cg.cs.tsinghua.edu.cn/people/~cmm/saliency/ |
| Code | Visual Tracking | Motion Tracking in Image Sequences | C. Stauffer and W. E. L. Grimson. Learning patterns of activity using real-time tracking, PAMI, 2000 | http://www.cs.berkeley.edu/~flw/tracker/ |
| Code | Saliency Detection | Itti, Koch, and Niebur' saliency detection | L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. PAMI, 1998 | http://www.saliencytoolbox.net/ |
| Code | Feature Detection,Feature Extraction, andAction Recognition | Space-Time Interest Points (STIP) | I. Laptev, On Space-Time Interest Points, IJCV, 2005 and I. Laptev and T. Lindeberg, On Space-Time Interest Points, IJCV 2005 | http://www.irisa.fr/vista/Equipe/People/Laptev/download/stip-1.1-winlinux.zip andhttp://www.nada.kth.se/cvap/abstracts/cvap284.html |
| Code | Texture Synthesis | Image Quilting for Texture Synthesis and Transfer | A. A. Efros and W. T. Freeman, Image Quilting for Texture Synthesis and Transfer, SIGGRAPH 2001 | http://www.cs.cmu.edu/~efros/quilt_research_code.zip |
| Code | Image Denoising | Non-local Means | | http://dmi.uib.es/~abuades/codis/NLmeansfilter.m |
| Code | Low-Rank Modeling | TILT: Transform Invariant Low-rank Textures | Z. Zhang, A. Ganesh, X. Liang, and Y. Ma, TILT: Transform Invariant Low-rank Textures, IJCV 2011 | http://perception.csl.uiuc.edu/matrix-rank/tilt.html |
| Code | Object Proposal | Objectness measure | B. Alexe, T. Deselaers, V. Ferrari, What is an Object?, CVPR 2010 | http://www.vision.ee.ethz.ch/~calvin/objectness/objectness-release-v1.01.tar.gz |
| Code | Image Filtering | Real-time O(1) Bilateral Filtering | Q. Yang, K.-H. Tan and N. Ahuja, Real-time O(1) Bilateral Filtering, CVPR 2009 | http://vision.ai.uiuc.edu/~qyang6/publications/code/qx_constant_time_bilateral_filter_ss.zip |
| Code | Image Quality Assessment | SPIQA | | http://vision.ai.uiuc.edu/~bghanem2/shared_code/SPIQA_code.zip |
| Code | Object Recognition | Biologically motivated object recognition | T. Serre, L. Wolf and T. Poggio. Object recognition with features inspired by visual cortex, CVPR 2005 | http://cbcl.mit.edu/software-datasets/standardmodel/index.html |
| Code | Illumination, Reflectance, and Shadow | Shadow Detection using Paired Region | R. Guo, Q. Dai and D. Hoiem, Single-Image Shadow Detection and Removal using Paired Regions, CVPR 2011 | http://www.cs.illinois.edu/homes/guo29/projects/shadow.html |
| Code | Illumination, Reflectance, and Shadow | Real-time Specular Highlight Removal | Q. Yang, S. Wang and N. Ahuja, Real-time Specular Highlight Removal Using Bilateral Filtering, ECCV 2010 | http://www.cs.cityu.edu.hk/~qiyang/publications/code/eccv-10.zip |
| Code | MRF Optimization | Max-flow/min-cut | Y. Boykov and V. Kolmogorov, An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision, PAMI 2004 | http://vision.csd.uwo.ca/code/maxflow-v3.01.zip |
| Code | Optical Flow | Optical Flow Evaluation | S. Baker et al. A Database and Evaluation Methodology for Optical Flow, IJCV, 2011 | http://vision.middlebury.edu/flow/ |
| Code | Image Super-resolution | MRF for image super-resolution | W. T Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 10. MIT Press, 2011 | http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution.html |
| Code | MRF Optimization | Planar Graph Cut | F. R. Schmidt, E. Toppe and D. Cremers, Efficient Planar Graph Cuts with Applications in Computer Vision, CVPR 2009 | http://vision.csd.uwo.ca/code/PlanarCut-v1.0.zip |
| Code | Object Detection | Feature Combination | P. Gehler and S. Nowozin, On Feature Combination for Multiclass Object Detection, ICCV, 2009 | http://www.vision.ee.ethz.ch/~pgehler/projects/iccv09/index.html |
| Code | Structure from motion | VisualSFM : A Visual Structure from Motion System | | http://www.cs.washington.edu/homes/ccwu/vsfm/ |
| Code | Nearest Neighbors Matching | ANN: Approximate Nearest Neighbor Searching | | http://www.cs.umd.edu/~mount/ANN/ |
| Code | Saliency Detection | Learning Hierarchical Image Representation with Sparsity, Saliency and Locality | J. Yang and M.-H. Yang, Learning Hierarchical Image Representation with Sparsity, Saliency and Locality, BMVC 2011 | |
| Code | Optical Flow | Optical Flow by Deqing Sun | D. Sun, S. Roth, M. J. Black, Secrets of Optical Flow Estimation and Their Principles, CVPR, 2010 | http://www.cs.brown.edu/~dqsun/code/flow_code.zip |
| Code | Image Understanding | Discriminative Models for Multi-Class Object Layout | C. Desai, D. Ramanan, C. Fowlkes. "Discriminative Models for Multi-Class Object Layout, IJCV 2011 | http://www.ics.uci.edu/~desaic/multiobject_context.zip |
| Code | Graph Matching | Hyper-graph Matching via Reweighted Random Walks | J. Lee, M. Cho, K. M. Lee. "Hyper-graph Matching via Reweighted Random Walks", CVPR 2011 | http://cv.snu.ac.kr/research/~RRWHM/ |
| Code | Object Detection | Hough Forests for Object Detection | J. Gall and V. Lempitsky, Class-Specific Hough Forests for Object Detection, CVPR, 2009 | http://www.vision.ee.ethz.ch/~gallju/projects/houghforest/index.html |
| Code | Object Discovery | Using Multiple Segmentations to Discover Objects and their Extent in Image Collections | B. Russell, A. A. Efros, J. Sivic, W. T. Freeman, A. Zisserman, Using Multiple Segmentations to Discover Objects and their Extent in Image Collections, CVPR 2006 | http://people.csail.mit.edu/brussell/research/proj/mult_seg_discovery/index.html |
| Code | Dimension Reduction | Diffusion maps | | http://www.stat.cmu.edu/~annlee/software.htm |
| Code | Multiple Kernel Learning | SHOGUN | S. Sonnenburg, G. Rätsch, C. Schäfer, B. Schölkopf . Large scale multiple kernel learning. JMLR, 2006 | http://www.shogun-toolbox.org/ |
| Code | Distance Transformation | Distance Transforms of Sampled Functions | | http://people.cs.uchicago.edu/~pff/dt/ |
| Code | Image Filtering | Image smoothing via L0 Gradient Minimization | L. Xu, C. Lu, Y. Xu, J. Jia, Image smoothing via L0 Gradient Minimization, SIGGRAPH Asia 2011 | http://www.cse.cuhk.edu.hk/~leojia/projects/L0smoothing/L0smoothing.zip |
| Code | Feature Extraction | PCA-SIFT | Y. Ke and R. Sukthankar, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors,CVPR, 2004 | http://www.cs.cmu.edu/~yke/pcasift/ |
| Code | Visual Tracking | Particle Filter Object Tracking | | http://blogs.oregonstate.edu/hess/code/particles/ |
| Code | Feature Extraction | sRD-SIFT | M. Lourenco, J. P. Barreto and A. Malti, Feature Detection and Matching in Images with Radial Distortion, ICRA 2010 | http://arthronav.isr.uc.pt/~mlourenco/srdsift/index.html# |
| Code | Multiple Instance Learning | MILES | Y. Chen, J. Bi and J. Z. Wang, MILES: Multiple-Instance Learning via Embedded Instance Selection. PAMI 2006 | http://infolab.stanford.edu/~wangz/project/imsearch/SVM/PAMI06/ |
| Code | Action Recognition | Dense Trajectories Video Description | H. Wang and A. Klaser and C. Schmid and C.- L. Liu, Action Recognition by Dense Trajectories, CVPR, 2011 | http://lear.inrialpes.fr/people/wang/dense_trajectories |
| Code | Image Segmentation | Efficient Graph-based Image Segmentation - C++ code | P. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004 | http://people.cs.uchicago.edu/~pff/segment/ |
| Code | Object Proposal | Parametric min-cut | J. Carreira and C. Sminchisescu. Constrained Parametric Min-Cuts for Automatic Object Segmentation, CVPR 2010 | http://sminchisescu.ins.uni-bonn.de/code/cpmc/ |
| Code | Common Visual Pattern Discovery | Common Visual Pattern Discovery via Spatially Coherent Correspondences | H. Liu, S. Yan, "Common Visual Pattern Discovery via Spatially Coherent Correspondences", CVPR 2010 | https://sites.google.com/site/lhrbss/home/papers/SimplifiedCode.zip?attredirects=0 |
| Code | Sparse Representation | Sparse coding simulation software | Olshausen BA, Field DJ, "Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images", Nature 1996 | http://redwood.berkeley.edu/bruno/sparsenet/ |
| Code | MRF Optimization | Max-flow/min-cut for massive grids | A. Delong and Y. Boykov, A Scalable Graph-Cut Algorithm for N-D Grids, CVPR 2008 | http://vision.csd.uwo.ca/code/regionpushrelabel-v1.03.zip |
| Code | Optical Flow | Horn and Schunck's Optical Flow | | http://www.cs.brown.edu/~dqsun/code/hs.zip |
| Code | Sparse Representation | Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing | M. Elad, Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing | http://www.cs.technion.ac.il/~elad/Various/Matlab-Package-Book.rar |
| Code | Image Understanding | Towards Total Scene Understanding | L.-J. Li, R. Socher and Li F.-F.. Towards Total Scene Understanding:Classification, Annotation and Segmentation in an Automatic Framework, CVPR 2009 | http://vision.stanford.edu/projects/totalscene/index.html |
| Code | Camera Calibration | Camera Calibration Toolbox for Matlab | http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/ref.html | http://www.vision.caltech.edu/bouguetj/calib_doc/ |
| Code | Image Segmentation | Turbepixels | A. Levinshtein, A. Stere, K. N. Kutulakos, D. J. Fleet, S. J. Dickinson, and K. Siddiqi, TurboPixels: Fast Superpixels Using Geometric Flows, PAMI 2009 | http://www.cs.toronto.edu/~babalex/research.html |
| Code | Feature Detection | Edge Foci Interest Points | L. Zitnickand K. Ramnath, Edge Foci Interest Points, ICCV, 2011 | http://research.microsoft.com/en-us/um/people/larryz/edgefoci/edge_foci.htm |
| Code | Feature Extraction | Local Self-Similarity Descriptor | E. Shechtman and M. Irani. Matching local self-similarities across images and videos, CVPR, 2007 | http://www.robots.ox.ac.uk/~vgg/software/SelfSimilarity/ |
| Code | Subspace Learning | Generalized Principal Component Analysis | R. Vidal, Y. Ma and S. Sastry. Generalized Principal Component Analysis (GPCA), CVPR 2003 | http://www.vision.jhu.edu/downloads/main.php?dlID=c1 |
| Code | Camera Calibration | EasyCamCalib | J. Barreto, J. Roquette, P. Sturm, and F. Fonseca, Automatic camera calibration applied to medical endoscopy, BMVC, 2009 | http://arthronav.isr.uc.pt/easycamcalib/ |
| Code | Image Segmentation | Superpixel by Gerg Mori | X. Ren and J. Malik. Learning a classification model for segmentation. ICCV, 2003 | http://www.cs.sfu.ca/~mori/research/superpixels/ |
| Code | Image Understanding | Object Bank | Li-Jia Li, Hao Su, Eric P. Xing and Li Fei-Fei. Object Bank: A High-Level Image Representation for Scene Classification and Semantic Feature Sparsification, NIPS 2010 | http://vision.stanford.edu/projects/objectbank/index.html |
| Code | Saliency Detection | Spectrum Scale Space based Visual Saliency | J Li, M D. Levine, X An and H. He, Saliency Detection Based on Frequency and Spatial Domain Analyses, BMVC 2011 | http://www.cim.mcgill.ca/~lijian/saliency.htm |
| Code | Sparse Representation | Fisher Discrimination Dictionary Learning for Sparse Representation | M. Yang, L. Zhang, X. Feng and D. Zhang, Fisher Discrimination Dictionary Learning for Sparse Representation, ICCV 2011 | http://www4.comp.polyu.edu.hk/~cslzhang/code/FDDL.zip |
| Code | Object Detection | Cascade Object Detection with Deformable Part Models | P. Felzenszwalb, R. Girshick, D. McAllester. Cascade Object Detection with Deformable Part Models. CVPR, 2010 | http://people.cs.uchicago.edu/~rbg/star-cascade/ |
| Code | Object Segmentation | Sparse to Dense Labeling | P. Ochs, T. Brox, Object Segmentation in Video: A Hierarchical Variational Approach for Turning Point Trajectories into Dense Regions, ICCV 2011 | http://lmb.informatik.uni-freiburg.de/resources/binaries/SparseToDenseLabeling.tar.gz |
| Code | Optical Flow | Dense Point Tracking | N. Sundaram, T. Brox, K. KeutzerDense point trajectories by GPU-accelerated large displacement optical flow, ECCV 2010 | http://lmb.informatik.uni-freiburg.de/resources/binaries/ |
| Code | Visual Tracking | Tracking with Online Multiple Instance Learning | B. Babenko, M.-H. Yang, S. Belongie, Visual Tracking with Online Multiple Instance Learning, PAMI 2011 | http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml |
| Code | Graph Matching | Reweighted Random Walks for Graph Matching | M. Cho, J. Lee, and K. M. Lee, Reweighted Random Walks for Graph Matching, ECCV 2010 | http://cv.snu.ac.kr/research/~RRWM/ |
| Code | Machine Learning | Statistical Pattern Recognition Toolbox | M.I. Schlesinger, V. Hlavac: Ten lectures on the statistical and structural pattern recognition, Kluwer Academic Publishers, 2002 | http://cmp.felk.cvut.cz/cmp/software/stprtool/ |
| Code | Image Super-resolution | Sprarse coding super-resolution | J. Yang, J. Wright, T. S. Huang, and Y. Ma. Image super-resolution via sparse representation, TIP 2010 | http://www.ifp.illinois.edu/~jyang29/ScSR.htm |
| Code | Object Detection | Discriminatively Trained Deformable Part Models | P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan.Object Detection with Discriminatively Trained Part Based Models, PAMI, 2010 | http://people.cs.uchicago.edu/~pff/latent/ |
| Code | Multiple Instance Learning | MIForests | C. Leistner, A. Saffari, and H. Bischof, MIForests: Multiple-Instance Learning with Randomized Trees, ECCV 2010 | http://www.ymer.org/amir/software/milforests/ |
| Code | Optical Flow | Large Displacement Optical Flow | T. Brox, J. Malik, Large displacement optical flow: descriptor matching in variational motion estimation, PAMI 2011 | http://lmb.informatik.uni-freiburg.de/resources/binaries/ |
| Code | Multiple View Geometry | MATLAB and Octave Functions for Computer Vision and Image Processing | P. D. Kovesi. MATLAB and Octave Functions for Computer Vision and Image Processing, http://www.csse.uwa.edu.au/~pk/research/matlabfns | http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/index.html |
| Code | Image Filtering | Anisotropic Diffusion | P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, PAMI 1990 | http://www.mathworks.com/matlabcentral/fileexchange/14995-anisotropic-diffusion-perona-malik |
| Code | Feature Detection andFeature Extraction | Geometric Blur | A. C. Berg, T. L. Berg, and J. Malik. Shape matching and object recognition using low distortion correspondences. CVPR, 2005 | http://www.robots.ox.ac.uk/~vgg/software/MKL/ |
| Code | Low-Rank Modeling | Low-Rank Matrix Recovery and Completion | | http://perception.csl.uiuc.edu/matrix-rank/sample_code.html |
| Code | Object Detection | A simple parts and structure object detector | ICCV 2005 short courses on Recognizing and Learning Object Categories | http://people.csail.mit.edu/fergus/iccv2005/partsstructure.html |
| Code | Kernels and Distances | Diffusion-based distance | H. Ling and K. Okada, Diffusion Distance for Histogram Comparison, CVPR 2006 | http://www.dabi.temple.edu/~hbling/code/DD_v1.zip |
| Code | Image Denoising | K-SVD | | http://www.cs.technion.ac.il/~ronrubin/Software/ksvdbox13.zip |
| Code | Multiple Kernel Learning | SimpleMKL | A. Rakotomamonjy, F. Bach, S. Canu, and Y. Grandvalet. Simplemkl. JMRL, 2008 | http://asi.insa-rouen.fr/enseignants/~arakotom/code/mklindex.html |
| Code | Feature Extraction | Pyramids of Histograms of Oriented Gradients (PHOG) | A. Bosch, A. Zisserman, and X. Munoz, Representing shape with a spatial pyramid kernel, CIVR, 2007 | http://www.robots.ox.ac.uk/~vgg/research/caltech/phog/phog.zip |
| Code | Sparse Representation | Efficient sparse coding algorithms | H. Lee, A. Battle, R. Rajat and A. Y. Ng, Efficient sparse coding algorithms, NIPS 2007 | http://ai.stanford.edu/~hllee/softwares/nips06-sparsecoding.htm |
| Code | Multi-View Stereo | Clustering Views for Multi-view Stereo | Y. Furukawa, B. Curless, S. M. Seitz, and R. Szeliski, Towards Internet-scale Multi-view Stereo, CVPR 2010 | http://grail.cs.washington.edu/software/cmvs/ |
| Code | Multi-View Stereo | Multi-View Stereo Evaluation | S. Seitz et al. A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, CVPR 2006 | http://vision.middlebury.edu/mview/ |
| Code | Structure from motion | Structure and Motion Toolkit in Matlab | | http://cms.brookes.ac.uk/staff/PhilipTorr/Code/code_page_4.htm |
| Code | Pose Estimation | Training Deformable Models for Localization | Ramanan, D. "Learning to Parse Images of Articulated Bodies." NIPS 2006 | http://www.ics.uci.edu/~dramanan/papers/parse/index.html |
| Code | Low-Rank Modeling | RASL: Robust Batch Alignment of Images by Sparse and Low-Rank Decomposition | Y. Peng, A. Ganesh, J. Wright, W. Xu, and Y. Ma, RASL: Robust Batch Alignment of Images by Sparse and Low-Rank Decomposition, CVPR 2010 | http://perception.csl.uiuc.edu/matrix-rank/rasl.html |
| Code | Dimension Reduction | ISOMAP | | http://isomap.stanford.edu/ |
| Code | Alpha Matting | Learning-based Matting | Y. Zheng and C. Kambhamettu, Learning Based Digital Matting, ICCV 2009 | http://www.mathworks.com/matlabcentral/fileexchange/31412 |
| Code | Image Segmentation | Normalized Cut | J. Shi and J Malik, Normalized Cuts and Image Segmentation, PAMI, 2000 | http://www.cis.upenn.edu/~jshi/software/ |
| Code | Image Denoising andStereo Matching | Efficient Belief Propagation for Early Vision | P. F. Felzenszwalb and D. P. Huttenlocher, Efficient Belief Propagation for Early Vision, IJCV, 2006 | http://www.cs.brown.edu/~pff/bp/ |
| Code | Sparse Representation | A Linear Subspace Learning Approach via Sparse Coding | L. Zhang, P. Zhu, Q. Hu and D. Zhang, “A Linear Subspace Learning Approach via Sparse Coding,” ICCV 2011 | http://www4.comp.polyu.edu.hk/~cslzhang/code/LSL_SC.zip |
| Code | Text Recognition | Neocognitron for handwritten digit recognition | K. Fukushima: "Neocognitron for handwritten digit recognition", Neurocomputing, 2003 | http://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=375 |
| Code | Image Classification | Sparse Coding for Image Classification | J. Yang, K. Yu, Y. Gong, T. Huang, Linear Spatial Pyramid Matching using Sparse Coding for Image Classification, CVPR, 2009 | http://www.ifp.illinois.edu/~jyang29/ScSPM.htm |
| Code | Nearest Neighbors Matching | LDAHash: Binary Descriptors for Matching in Large Image Databases | C. Strecha, A. M. Bronstein, M. M. Bronstein and P. Fua. LDAHash: Improved matching with smaller descriptors, PAMI, 2011. | http://cvlab.epfl.ch/research/detect/ldahash/index.php |
| Code | Object Segmentation | ClassCut for Unsupervised Class Segmentation | B. Alexe, T. Deselaers and V. Ferrari, ClassCut for Unsupervised Class Segmentation, ECCV 2010 | http://www.vision.ee.ethz.ch/~calvin/classcut/ClassCut-release.zip |
| Code | Image Quality Assessment | Feature SIMilarity Index | | http://www4.comp.polyu.edu.hk/~cslzhang/IQA/FSIM/FSIM.htm |
| Code | Saliency Detection | Attention via Information Maximization | N. Bruce and J. Tsotsos. Saliency based on information maximization. In NIPS, 2005 | http://www.cse.yorku.ca/~neil/AIM.zip |
| Code | Image Denoising | What makes a good model of natural images ? | Y. Weiss and W. T. Freeman, CVPR 2007 | http://www.cs.huji.ac.il/~yweiss/BRFOE.zip |
| Code | Image Segmentation | Mean-Shift Image Segmentation - Matlab Wrapper | D. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002 | http://www.wisdom.weizmann.ac.il/~bagon/matlab_code/edison_matlab_interface.tar.gz |
| Code | Object Segmentation | Geodesic Star Convexity for Interactive Image Segmentation | V. Gulshan, C. Rother, A. Criminisi, A. Blake and A. Zisserman. Geodesic star convexity for interactive image segmentation | http://www.robots.ox.ac.uk/~vgg/software/iseg/index.shtml |
| Code | Feature Detection andFeature Extraction | Affine-SIFT | J.M. Morel and G.Yu, ASIFT, A new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences, 2009 | http://www.ipol.im/pub/algo/my_affine_sift/ |
| Code | MRF Optimization | Multi-label optimization | Y. Boykov, O. Verksler, and R. Zabih, Fast Approximate Energy Minimization via Graph Cuts, PAMI 2001 | http://vision.csd.uwo.ca/code/gco-v3.0.zip |
| Code | Feature Detection andFeature Extraction | Scale-invariant feature transform (SIFT) - Demo Software | D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004. | http://www.cs.ubc.ca/~lowe/keypoints/ |
| Code | Visual Tracking | KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker | B. D. Lucas and T. Kanade. An Iterative Image Registration Technique with an Application to Stereo Vision. IJCAI, 1981 | http://www.ces.clemson.edu/~stb/klt/ |
| Code | Feature Detection andFeature Extraction | Affine Covariant Features | T. Tuytelaars and K. Mikolajczyk, Local Invariant Feature Detectors: A Survey, Foundations and Trends in Computer Graphics and Vision, 2008 | http://www.robots.ox.ac.uk/~vgg/research/affine/ |
| Code | Image Segmentation | Segmenting Scenes by Matching Image Composites | B. Russell, A. A. Efros, J. Sivic, W. T. Freeman, A. Zisserman, NIPS 2009 | http://www.cs.washington.edu/homes/bcr/projects/SceneComposites/index.html |
| Code | Image Segmentation | OWT-UCM Hierarchical Segmentation | P. Arbelaez, M. Maire, C. Fowlkes and J. Malik. Contour Detection and Hierarchical Image Segmentation. PAMI, 2011 | http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html |
| Code | Feature Matching andImage Classification | The Pyramid Match: Efficient Matching for Retrieval and Recognition | K. Grauman and T. Darrell. The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, ICCV 2005 | http://www.cs.utexas.edu/~grauman/research/projects/pmk/pmk_projectpage.htm |
| Code | Alpha Matting | Bayesian Matting | Y. Y. Chuang, B. Curless, D. H. Salesin, and R. Szeliski, A Bayesian Approach to Digital Matting, CVPR, 2001 | http://www1.idc.ac.il/toky/CompPhoto-09/Projects/Stud_projects/Miki/index.html |
| Code | Image Deblurring | Richardson-Lucy Deblurring for Scenes under Projective Motion Path | Y.-W. Tai, P. Tan, M. S. Brown: Richardson-Lucy Deblurring for Scenes under Projective Motion Path, PAMI 2011 | http://yuwing.kaist.ac.kr/projects/projectivedeblur/projectivedeblur_files/ProjectiveDeblur.zip |
| Code | Pose Estimation | Articulated Pose Estimation using Flexible Mixtures of Parts | Y. Yang, D. Ramanan, Articulated Pose Estimation using Flexible Mixtures of Parts, CVPR 2011 | http://phoenix.ics.uci.edu/software/pose/ |
| Code | Feature Extraction | BRIEF: Binary Robust Independent Elementary Features | M. Calonder, V. Lepetit, C. Strecha, P. Fua, BRIEF: Binary Robust Independent Elementary Features, ECCV 2010 | http://cvlab.epfl.ch/research/detect/brief/ |
| Code | Feature Extraction | Global and Efficient Self-Similarity | T. Deselaers and V. Ferrari. Global and Efficient Self-Similarity for Object Classification and Detection. CVPR 2010 and T. Deselaers, V. Ferrari, Global and Efficient Self-Similarity for Object Classification and Detection, CVPR 2010 | http://www.vision.ee.ethz.ch/~calvin/gss/selfsim_release1.0.tgz |
| Code | Image Super-resolution | Multi-frame image super-resolution | Pickup, L. C. Machine Learning in Multi-frame Image Super-resolution, PhD thesis | http://www.robots.ox.ac.uk/~vgg/software/SR/index.html |
| Code | Feature Detection andFeature Extraction | Scale-invariant feature transform (SIFT) - Library | D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004. | http://blogs.oregonstate.edu/hess/code/sift/ |
| Code | Image Denoising | Clustering-based Denoising | P. Chatterjee and P. Milanfar, Clustering-based Denoising with Locally Learned Dictionaries (K-LLD), TIP, 2009 | http://users.soe.ucsc.edu/~priyam/K-LLD/ |
| Code | Object Recognition | Recognition by Association via Learning Per-exemplar Distances | T. Malisiewicz, A. A. Efros, Recognition by Association via Learning Per-exemplar Distances, CVPR 2008 | http://www.cs.cmu.edu/~tmalisie/projects/cvpr08/dfuns.tar.gz |
| Code | Visual Tracking | Superpixel Tracking | S. Wang, H. Lu, F. Yang, and M.-H. Yang, Superpixel Tracking, ICCV 2011 | http://faculty.ucmerced.edu/mhyang/papers/iccv11a.html |
| Code | Sparse Representation | SPArse Modeling Software | J. Mairal, F. Bach, J. Ponce and G. Sapiro. Online Learning for Matrix Factorization and Sparse Coding, JMLR 2010 | http://www.di.ens.fr/willow/SPAMS/ |
| Code | Saliency Detection | Saliency detection: A spectral residual approach | X. Hou and L. Zhang. Saliency detection: A spectral residual approach. CVPR, 2007 | http://www.klab.caltech.edu/~xhou/projects/spectralResidual/spectralresidual.html |
| Code | Image Filtering | Guided Image Filtering | K. He, J. Sun, X. Tang, Guided Image Filtering, ECCV 2010 | http://personal.ie.cuhk.edu.hk/~hkm007/eccv10/guided-filter-code-v1.rar |
| Code | Kernels and Distances | Fast Directional Chamfer Matching | | http://www.umiacs.umd.edu/~mingyliu/src/fdcm_matlab_wrapper_v0.2.zip |
| Code | Visual Tracking | L1 Tracking | X. Mei and H. Ling, Robust Visual Tracking using L1 Minimization, ICCV, 2009 | http://www.dabi.temple.edu/~hbling/code_data.htm |
| Code | Object Proposal | Region-based Object Proposal | I. Endres and D. Hoiem. Category Independent Object Proposals, ECCV 2010 | http://vision.cs.uiuc.edu/proposals/ |
| Code | Object Detection | Ensemble of Exemplar-SVMs for Object Detection and Beyond | T. Malisiewicz, A. Gupta, A. A. Efros, Ensemble of Exemplar-SVMs for Object Detection and Beyond , ICCV 2011 | http://www.cs.cmu.edu/~tmalisie/projects/iccv11/ |
| Code | Dimension Reduction | Dimensionality Reduction Toolbox | | http://homepage.tudelft.nl/19j49/Matlab_Toolbox_for_Dimensionality_Reduction.html |
| Code | Object Detection | Viola-Jones Object Detection | P. Viola and M. Jones, Rapid Object Detection Using a Boosted Cascade of Simple Features, CVPR, 2001 | http://pr.willowgarage.com/wiki/FaceDetection |
| Code | Object Detection | Implicit Shape Model | B. Leibe, A. Leonardis, B. Schiele. Robust Object Detection with Interleaved Categorization and Segmentation, IJCV, 2008 | http://www.vision.ee.ethz.ch/~bleibe/code/ism.html |
| Code | Saliency Detection | Saliency detection using maximum symmetric surround | R. Achanta and S. Susstrunk. Saliency detection using maximum symmetric surround. In ICIP, 2010 | http://ivrg.epfl.ch/supplementary_material/RK_ICIP2010/index.html |
| Code | Image Filtering | Fast Bilateral Filter | S. Paris and F. Durand, A Fast Approximation of the Bilateral Filter using a Signal Processing Approach, ECCV, 2006 | http://people.csail.mit.edu/sparis/bf/ |
| Code | Machine Learning | FastICA package for MATLAB | http://research.ics.tkk.fi/ica/book/ | http://research.ics.tkk.fi/ica/fastica/ |
| Code | Feature Detection andFeature Extraction | Maximally stable extremal regions (MSER) | J. Matas, O. Chum, M. Urba, and T. Pajdla. Robust wide baseline stereo from maximally stable extremal regions. BMVC, 2002 | http://www.robots.ox.ac.uk/~vgg/research/affine/ |
| Code | Structure from motion | Bundler | N. Snavely, S M. Seitz, R Szeliski. Photo Tourism: Exploring image collections in 3D. SIGGRAPH 2006 | http://phototour.cs.washington.edu/bundler/ |
| Code | Visual Tracking | Online Discriminative Object Tracking with Local Sparse Representation | Q. Wang, F. Chen, W. Xu, and M.-H. Yang, Online Discriminative Object Tracking with Local Sparse Representation, WACV 2012 | http://faculty.ucmerced.edu/mhyang/code/wacv12a_code.zip |
| Code | Alpha Matting | Closed Form Matting | A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting, PAMI 2008. | http://people.csail.mit.edu/alevin/matting.tar.gz |
| Code | Image Filtering | GradientShop | P. Bhat, C.L. Zitnick, M. Cohen, B. Curless, and J. Kim, GradientShop: A Gradient-Domain Optimization Framework for Image and Video Filtering, TOG 2010 | http://grail.cs.washington.edu/projects/gradientshop/ |
| Code | Visual Tracking | Incremental Learning for Robust Visual Tracking | D. Ross, J. Lim, R.-S. Lin, M.-H. Yang, Incremental Learning for Robust Visual Tracking, IJCV 2007 | http://www.cs.toronto.edu/~dross/ivt/ |
| Code | Feature Detection andFeature Extraction | Color Descriptor | K. E. A. van de Sande, T. Gevers and Cees G. M. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, PAMI, 2010 | http://koen.me/research/colordescriptors/ |
| Code | Image Segmentation | Entropy Rate Superpixel Segmentation | M.-Y. Liu, O. Tuzel, S. Ramalingam, and R. Chellappa, Entropy Rate Superpixel Segmentation, CVPR 2011 | http://www.umiacs.umd.edu/~mingyliu/src/ers_matlab_wrapper_v0.1.zip |
| Code | Image Filtering | Domain Transformation | E. Gastal, M. Oliveira, Domain Transform for Edge-Aware Image and Video Processing, SIGGRAPH 2011 | http://inf.ufrgs.br/~eslgastal/DomainTransform/DomainTransformFilters-Source-v1.0.zip |
| Code | Multiple Kernel Learning | OpenKernel.org | F. Orabona and L. Jie. Ultra-fast optimization algorithm for sparse multi kernel learning. ICML, 2011 | http://www.openkernel.org/ |
| Code | Image Segmentation | Efficient Graph-based Image Segmentation - Matlab Wrapper | P. Felzenszwalb and D. Huttenlocher. Efficient Graph-Based Image Segmentation, IJCV 2004 | http://www.mathworks.com/matlabcentral/fileexchange/25866-efficient-graph-based-image-segmentation |
| Code | Image Segmentation | Biased Normalized Cut | S. Maji, N. Vishnoi and J. Malik, Biased Normalized Cut, CVPR 2011 | http://www.cs.berkeley.edu/~smaji/projects/biasedNcuts/ |
| Code | Stereo | Constant-Space Belief Propagation | Q. Yang, L. Wang, and N. Ahuja, A Constant-Space Belief Propagation Algorithm for Stereo Matching, CVPR 2010 | http://www.cs.cityu.edu.hk/~qiyang/publications/code/cvpr-10-csbp/csbp.htm |
| Code | Feature Detection andFeature Extraction | Speeded Up Robust Feature (SURF) - Open SURF | H. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006 | http://www.chrisevansdev.com/computer-vision-opensurf.html |
| Code | Visual Tracking | Online boosting trackers | H. Grabner, and H. Bischof, On-line Boosting and Vision, CVPR, 2006 | http://www.vision.ee.ethz.ch/boostingTrackers/ |
| Code | Image Denoising | Sparsity-based Image Denoising | W. Dong, X. Li, L. Zhang and G. Shi, Sparsity-based Image Denoising vis Dictionary Learning and Structural Clustering, CVPR, 2011 | http://www.csee.wvu.edu/~xinl/CSR.html |
| Code | Feature Detection andFeature Extraction | Scale-invariant feature transform (SIFT) - VLFeat | D. Lowe. Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004. | http://www.vlfeat.org/ |
| Code | Clustering | Spectral Clustering - UW Project | | http://www.stat.washington.edu/spectral/ |
| Code | Image Deblurring | Analyzing spatially varying blur | A. Chakrabarti, T. Zickler, and W. T. Freeman, Analyzing Spatially-varying Blur, CVPR 2010 | http://www.eecs.harvard.edu/~ayanc/svblur/ |
| Code | Multiple Instance Learning | DD-SVM | Yixin Chen and James Z. Wang, Image Categorization by Learning and Reasoning with Regions, JMLR 2004 | |
| Code | Feature Extraction | GIST Descriptor | A. Oliva and A. Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope, IJCV, 2001 | http://people.csail.mit.edu/torralba/code/spatialenvelope/ |
| Code | Image Classification | Texture Classification | M. Varma and A. Zisserman, A statistical approach to texture classification from single images, IJCV2005 | http://www.robots.ox.ac.uk/~vgg/research/texclass/index.html |
| Code | Structure from motion | Nonrigid Structure From Motion in Trajectory Space | | http://cvlab.lums.edu.pk/nrsfm/index.html |
| Code | Alpha Matting | Shared Matting | E. S. L. Gastal and M. M. Oliveira, Computer Graphics Forum, 2010 | http://www.inf.ufrgs.br/~eslgastal/SharedMatting/ |
| Code | Action Recognition | 3D Gradients (HOG3D) | A. Klaser, M. Marszałek, and C. Schmid, BMVC, 2008. | http://lear.inrialpes.fr/people/klaeser/research_hog3d |
| Code | Image Denoising | Kernel Regressions | | http://www.soe.ucsc.edu/~htakeda/MatlabApp/KernelRegressionBasedImageProcessingToolBox_ver1-1beta.zip |
| Code | Feature Detection | Boundary Preserving Dense Local Regions | J. Kim and K. Grauman, Boundary Preserving Dense Local Regions, CVPR 2011 | http://vision.cs.utexas.edu/projects/bplr/bplr.html |
| Code | Image Understanding | SuperParsing | J. Tighe and S. Lazebnik, SuperParsing: Scalable Nonparametric ImageParsing with Superpixels, ECCV 2010 | http://www.cs.unc.edu/~jtighe/Papers/ECCV10/eccv10-jtighe-code.zip |
| Code | Image Filtering | Weighted Least Squares Filter | Z. Farbman, R. Fattal, D. Lischinski, R. Szeliski, Edge-Preserving Decompositions for Multi-Scale Tone and Detail Manipulation, SIGGRAPH 2008 | http://www.cs.huji.ac.il/~danix/epd/ |
| Code | Image Super-resolution | Single-Image Super-Resolution Matlab Package | R. Zeyde, M. Elad, and M. Protter, On Single Image Scale-Up using Sparse-Representations, LNCS 2010 | http://www.cs.technion.ac.il/~elad/Various/Single_Image_SR.zip |
| Code | Image Understanding | Blocks World Revisited: Image Understanding using Qualitative Geometry and Mechanics | A. Gupta, A. A. Efros, M. Hebert, Blocks World Revisited: Image Understanding using Qualitative Geometry and Mechanics, ECCV 2010 | http://www.cs.cmu.edu/~abhinavg/blocksworld/#downloads |
| Code | Feature Extraction | Shape Context | S. Belongie, J. Malik and J. Puzicha. Shape matching and object recognition using shape contexts, PAMI, 2002 | http://www.eecs.berkeley.edu/Research/Projects/CS/vision/shape/sc_digits.html |
| Code | Image Processing andImage Filtering | Piotr's Image & Video Matlab Toolbox | Piotr Dollar, Piotr's Image & Video Matlab Toolbox, http://vision.ucsd.edu/~pdollar/toolbox/doc/index.html | http://vision.ucsd.edu/~pdollar/toolbox/doc/index.html |
| Code | Illumination, Reflectance, and Shadow | Webcam Clip Art: Appearance and Illuminant Transfer from Time-lapse Sequences | J-F. Lalonde, A. A. Efros, S. G. Narasimhan, Webcam Clip Art: Appearance and Illuminant Transfer from Time-lapse Sequences, SIGGRAPH Asia 2009 | http://www.cs.cmu.edu/~jlalonde/software.html#skyModel |
| Code | Pose Estimation | Calvin Upper-Body Detector | E. Marcin, F. Vittorio, Better Appearance Models for Pictorial Structures, BMVC 2009 | http://www.vision.ee.ethz.ch/~calvin/calvin_upperbody_detector/ |
| Code | Image Classification | Locality-constrained Linear Coding | J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained Linear Coding for Image Classification, CVPR, 2010 | http://www.ifp.illinois.edu/~jyang29/LLC.htm |
| Code | Feature Detection andFeature Extraction | Speeded Up Robust Feature (SURF) - Matlab Wrapper | H. Bay, T. Tuytelaars and L. V. Gool SURF: Speeded Up Robust Features, ECCV, 2006 | http://www.maths.lth.se/matematiklth/personal/petter/surfmex.php |
| Code | Pose Estimation | Estimating Human Pose from Occluded Images | J.-B. Huang and M.-H. Yang, Estimating Human Pose from Occluded Images, ACCV 2009 | http://faculty.ucmerced.edu/mhyang/code/accv09_pose.zip |
| Code | Structure from motion | OpenSourcePhotogrammetry | | http://opensourcephotogrammetry.blogspot.com/ |
| Code | Image Classification | Spatial Pyramid Matching | S. Lazebnik, C. Schmid, and J. Ponce. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, CVPR 2006 | http://www.cs.unc.edu/~lazebnik/research/SpatialPyramid.zip |
| Code | Nearest Neighbors Matching | Coherency Sensitive Hashing | S. Korman, S. Avidan, Coherency Sensitive Hashing, ICCV 2011 | http://www.eng.tau.ac.il/~simonk/CSH/index.html |
| Code | Image Segmentation | Segmentation by Minimum Code Length | A. Y. Yang, J. Wright, S. Shankar Sastry, Y. Ma , Unsupervised Segmentation of Natural Images via Lossy Data Compression, CVIU, 2007 | http://perception.csl.uiuc.edu/coding/image_segmentation/ |
| Code | Saliency Detection | Frequency-tuned salient region detection | R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk. Frequency-tuned salient region detection. In CVPR, 2009 | http://ivrgwww.epfl.ch/supplementary_material/RK_CVPR09/index.html |
| Code | MRF Optimization | Max-flow/min-cut for shape fitting | V. Lempitsky and Y. Boykov, Global Optimization for Shape Fitting, CVPR 2007 | http://www.csd.uwo.ca/faculty/yuri/Implementations/TouchExpand.zip |
| Code | Feature Detection | Canny Edge Detection | J. Canny, A Computational Approach To Edge Detection, PAMI, 1986 | http://www.mathworks.com/help/toolbox/images/ref/edge.html |
| Code | Object Detection | Multiple Kernels | A. Vedaldi, V. Gulshan, M. Varma, and A. Zisserman, Multiple Kernels for Object Detection. ICCV, 2009 | http://www.robots.ox.ac.uk/~vgg/software/MKL/ |
| Code | Image Segmentation | Mean-Shift Image Segmentation - EDISON | D. Comaniciu, P Meer. Mean Shift: A Robust Approach Toward Feature Space Analysis. PAMI 2002 | http://coewww.rutgers.edu/riul/research/code/EDISON/index.html |
| Code | Image Quality Assessment | Degradation Model | | http://users.ece.utexas.edu/~bevans/papers/2000/imageQuality/index.html |
| Code | Object Detection | Ensemble of Exemplar-SVMs | T. Malisiewicz, A. Gupta, A. Efros. Ensemble of Exemplar-SVMs for Object Detection and Beyond . ICCV, 2011 | http://www.cs.cmu.edu/~tmalisie/projects/iccv11/ |
| Code | Image Deblurring | Radon Transform | T. S. Cho, S. Paris, B. K. P. Horn, W. T. Freeman, Blur kernel estimation using the radon transform, CVPR 2011 | http://people.csail.mit.edu/taegsang/Documents/RadonDeblurringCode.zip |
| Code | Image Deblurring | Eficient Marginal Likelihood Optimization in Blind Deconvolution | A. Levin, Y. Weiss, F. Durand, W. T. Freeman. Efficient Marginal Likelihood Optimization in Blind Deconvolution, CVPR 2011 | http://www.wisdom.weizmann.ac.il/~levina/papers/LevinEtalCVPR2011Code.zip |
| Code | Feature Detection | FAST Corner Detection | E. Rosten and T. Drummond, Machine learning for high-speed corner detection, ECCV, 2006 | http://www.edwardrosten.com/work/fast.html |
| Code | Image Super-resolution | MDSP Resolution Enhancement Software | S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, Fast and Robust Multi-frame Super-resolution, TIP 2004 | http://users.soe.ucsc.edu/~milanfar/software/superresolution.html |
| Code | Feature Extraction andObject Detection | Histogram of Oriented Graidents - INRIA Object Localization Toolkit | N. Dalal and B. Triggs. Histograms of Oriented Gradients for Human Detection. CVPR 2005 | http://www.navneetdalal.com/software |
| Code | Visual Tracking | Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects | H. Pirsiavash, D. Ramanan, C. Fowlkes. "Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects, CVPR 2011 | http://www.ics.uci.edu/~hpirsiav/papers/tracking_cvpr11_release_v1.0.tar.gz |
| Code | Saliency Detection | Segmenting salient objects from images and videos | E. Rahtu, J. Kannala, M. Salo, and J. Heikkila. Segmenting salient objects from images and videos. CVPR, 2010 | http://www.cse.oulu.fi/MVG/Downloads/saliency |
| Code | Visual Tracking | Object Tracking | A. Yilmaz, O. Javed and M. Shah, Object Tracking: A Survey, ACM Journal of Computing Surveys, Vol. 38, No. 4, 2006 | http://plaza.ufl.edu/lvtaoran/object%20tracking.htm |
| Code | Machine Learning | Boosting Resources by Liangliang Cao | http://www.ifp.illinois.edu/~cao4/reading/boostingbib.htm | http://www.ifp.illinois.edu/~cao4/reading/boostingbib.htm |
| Code | Machine Learning | Netlab Neural Network Software | C. M. Bishop, Neural Networks for Pattern RecognitionㄝOxford University Press, 1995 | http://www1.aston.ac.uk/eas/research/groups/ncrg/resources/netlab/ |
| Code | Optical Flow | Classical Variational Optical Flow | T. Brox, A. Bruhn, N. Papenberg, J. Weickert, High accuracy optical flow estimation based on a theory for warping, ECCV 2004 | http://lmb.informatik.uni-freiburg.de/resources/binaries/ |
| Code | Sparse Representation | Centralized Sparse Representation for Image Restoration | W. Dong, L. Zhang and G. Shi, “Centralized Sparse Representation for Image Restoration,” ICCV 2011 | http://www4.comp.polyu.edu.hk/~cslzhang/code/CSR_IR.zip |
| Course | Computer Vision | Introduction to Computer Vision, Stanford University, Winter 2010-2011 | Fei-Fei Li | http://vision.stanford.edu/teaching/cs223b/ |
| Course | Computer Vision | Computer Vision: From 3D Reconstruction to Visual Recognition, Fall 2012 | Silvio Savarese and Fei-Fei Li | https://www.coursera.org/course/computervision |
| Course | Computer Vision | Computer Vision, University of Texas at Austin, Spring 2011 | Kristen Grauman | http://www.cs.utexas.edu/~grauman/courses/spring2011/index.html |
| Course | Computer Vision | Learning-Based Methods in Vision, CMU, Spring 2012 | Alexei “Alyosha” Efros and Leonid Sigal | https://docs.google.com/document/pub?id=1jGBn7zPDEaU33fJwi3YI_usWS-U6gpSSJotV_2gDrL0 |
| Course | Visual Recognition | Visual Recognition, University of Texas at Austin, Fall 2011 | Kristen Grauman | http://www.cs.utexas.edu/~grauman/courses/fall2011/schedule.html |
| Course | Computer Vision | Introduction to Computer Vision | James Hays, Brown University, Fall 2011 | http://www.cs.brown.edu/courses/cs143/ |
| Course | Computer Vision | Computer Vision, University of North Carolina at Chapel Hill, Spring 2010 | Svetlana Lazebnik | http://www.cs.unc.edu/~lazebnik/spring10/ |
| Course | Computer Vision | Computer Vision: The Fundamentals, University of California at Berkeley, Fall 2012 | Jitendra Malik | https://www.coursera.org/course/vision |
| Course | Computational Photography | Computational Photography, University of Illinois, Urbana-Champaign, Fall 2011 | Derek Hoiem | http://www.cs.illinois.edu/class/fa11/cs498dh/ |
| Course | Graphical Models | Inference in Graphical Models, Stanford University, Spring 2012 | Andrea Montanari, Stanford University | http://www.stanford.edu/~montanar/TEACHING/Stat375/stat375.html |
| Course | Computer Vision | Computer Vision, New York University, Fall 2012 | Rob Fergus | http://cs.nyu.edu/~fergus/teaching/vision_2012/index.html |
| Course | Computer Vision | Advances in Computer Vision | Antonio Torralba, MIT, Spring 2010 | http://groups.csail.mit.edu/vision/courses/6.869/ |
| Course | Computer Vision | Computer Vision, University of Illinois, Urbana-Champaign, Spring 2012 | Derek Hoiem | http://www.cs.illinois.edu/class/sp12/cs543/ |
| Course | Computational Photography | Computational Photography, CMU, Fall 2011 | Alexei “Alyosha” Efros | http://graphics.cs.cmu.edu/courses/15-463/2011_fall/463.html |
| Course | Computer Vision | Computer Vision, University of Washington, Winter 2012 | Steven Seitz | http://www.cs.washington.edu/education/courses/cse455/12wi/ |
| Link | Source code | Source Code Collection for Reproducible Research | collected by Xin Li, Lane Dept of CSEE, West Virginia University | http://www.csee.wvu.edu/~xinl/reproducible_research.html |
| Link | Computer Vision | Computer Image Analysis, Computer Vision Conferences | USC | http://iris.usc.edu/information/Iris-Conferences.html |
| Link | Computer Vision | CV Papers on the web | CVPapers | http://www.cvpapers.com/index.html |
| Link | Computer Vision | CVonline | CVonline: The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision | http://homepages.inf.ed.ac.uk/rbf/CVonline/ |
| Link | Dataset | Compiled list of recognition datasets | compiled by Kristen Grauman | http://www.cs.utexas.edu/~grauman/courses/spring2008/datasets.htm |
| Link | Computer Vision | Annotated Computer Vision Bibliography | compiled by Keith Price | http://iris.usc.edu/Vision-Notes/bibliography/contents.html |
| Link | Computer Vision | The Computer Vision homepage | | http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html |
| Link | Computer Vision Industry | The Computer Vision Industry | David Lowe | http://www.cs.ubc.ca/~lowe/vision.html |
| Link | Source code | Computer Vision Algorithm Implementations | CVPapers | http://www.cvpapers.com/rr.html |
| Link | Computer Vision | CV Datasets on the web | CVPapers | http://www.cvpapers.com/datasets.html |
| Talk | Visual Recognition | Understanding Visual Scenes | Antonio Torralba, MIT | http://videolectures.net/nips09_torralba_uvs/ |
| Talk | Neuroscience | Learning in Hierarchical Architectures: from Neuroscience to Derived Kernels | Tomaso A. Poggio, McGovern Institute for Brain Research, Massachusetts Institute of Technology | http://videolectures.net/mlss09us_poggio_lhandk/ |
| Talk | Deep Learning | A tutorial on Deep Learning | Geoffrey E. Hinton, Department of Computer Science, University of Toronto | http://videolectures.net/jul09_hinton_deeplearn/ |
| Talk | Boosting | Theory and Applications of Boosting | Robert Schapire, Department of Computer Science, Princeton University | http://videolectures.net/mlss09us_schapire_tab/ |
| Talk | Graphical Models | Graphical Models and message-passing algorithms | Martin J. Wainwright, University of California at Berkeley | http://videolectures.net/mlss2011_wainwright_messagepassing/ |
| Talk | Statistical Learning Theory | Statistical Learning Theory | John Shawe-Taylor, Centre for Computational Statistics and Machine Learning, University College London | http://videolectures.net/mlss04_taylor_slt/ |
| Talk | Gaussian Process | Gaussian Process Basics | David MacKay, University of Cambridge | http://videolectures.net/gpip06_mackay_gpb/ |
| Talk | Information Theory | Information Theory | David MacKay, University of Cambridge | http://videolectures.net/mlss09uk_mackay_it/ |
| Talk | Optimization | Optimization Algorithms in Machine Learning | Stephen J. Wright, Computer Sciences Department, University of Wisconsin - Madison | http://videolectures.net/nips2010_wright_oaml/ |
| Talk | Bayesian Inference | Introduction To Bayesian Inference | Christopher Bishop, Microsoft Research | http://videolectures.net/mlss09uk_bishop_ibi/ |
| Talk | Bayesian Nonparametrics | Modern Bayesian Nonparametrics | Peter Orbanz and Yee Whye Teh | http://www.youtube.com/watch?v=F0_ih7THV94&feature=relmfu |
| Talk | Kernels and Distances | Machine learning and kernel methods for computer vision | Francis R. Bach, INRIA | http://videolectures.net/etvc08_bach_mlakm/ |
| Talk | Optimization | Convex Optimization | Lieven Vandenberghe, Electrical Engineering Department, University of California, Los Angeles | http://videolectures.net/mlss2011_vandenberghe_convex/ |
| Talk | Optimization | Energy Minimization with Label costs and Applications in Multi-Model Fitting | Yuri Boykov, Department of Computer Science, University of Western Ontario | http://videolectures.net/nipsworkshops2010_boykov_eml/ |
| Talk | Object Detection | Object Recognition with Deformable Models | Pedro Felzenszwalb, Brown University | http://www.youtube.com/watch?v=_J_clwqQ4gI |
| Talk | Low-level vision | Learning and Inference in Low-Level Vision | Yair Weiss, School of Computer Science and Engineering, The Hebrew University of Jerusalem | http://videolectures.net/nips09_weiss_lil/ |
| Talk | 3D Computer Vision | 3D Computer Vision: Past, Present, and Future | Steven Seitz, University of Washington, Google Tech Talk, 2011 | http://www.youtube.com/watch?v=kyIzMr917Rc |
| Talk | Optimization | Who is Afraid of Non-Convex Loss Functions? | Yann LeCun, New York University | http://videolectures.net/eml07_lecun_wia/ |
| Talk | Sparse Representation | Sparse Methods for Machine Learning: Theory and Algorithms | Francis R. Bach, INRIA | http://videolectures.net/nips09_bach_smm/ |
| Talk | Optimization and Support Vector Machines | Optimization Algorithms in Support Vector Machines | Stephen J. Wright, Computer Sciences Department, University of Wisconsin - Madison | http://videolectures.net/mlss09us_wright_oasvm/ |
| Talk | Information Theory | Information Theory in Learning and Control | Naftali (Tali) Tishby, The Hebrew University | http://www.youtube.com/watch?v=GKm53xGbAOk&feature=relmfu |
| Talk | Relative Entropy | Relative Entropy | Sergio Verdu, Princeton University | http://videolectures.net/nips09_verdu_re/ |
| Tutorial | Object Detection | Geometry constrained parts based detection | Simon Lucey, Jason Saragih, ICCV 2011 Tutorial | http://ci2cv.net/tutorials/iccv-2011/ |
| Tutorial | Graphical Models | Learning with inference for discrete graphical models | Nikos Komodakis, Pawan Kumar, Nikos Paragios, Ramin Zabih, ICCV 2011 Tutorial | http://www.csd.uoc.gr/~komod/ICCV2011_tutorial/ |
| Tutorial | Variational Calculus | Variational methods for computer vision | Daniel Cremers, Bastian Goldlucke, Thomas Pock, ICCV 2011 Tutorial | http://cvpr.in.tum.de/tutorials/iccv2011 |
| Tutorial | 3D perception | Computer Vision and 3D Perception for Robotics | Radu Bogdan Rusu, Gary Bradski, Caroline Pantofaru, Stefan Hinterstoisser, Stefan Holzer, Kurt Konolige and Andrea Vedaldi, ECCV 2010 Tutorial | http://www.willowgarage.com/workshops/2010/eccv |
| Tutorial | Action Recognition | Looking at people: The past, the present and the future | L. Sigal, T. Moeslund, A. Hilton, V. Kruger, ICCV 2011 Tutorial | http://www.cs.brown.edu/~ls/iccv2011tutorial.html |
| Tutorial | Non-linear Least Squares | Computer vision fundamentals: robust non-linear least-squares and their applications | Pascal Fua, Vincent Lepetit, ICCV 2011 Tutorial | http://cvlab.epfl.ch/~fua/courses/lsq/ |
| Tutorial | Action Recognition | Frontiers of Human Activity Analysis | J. K. Aggarwal, Michael S. Ryoo, and Kris Kitani, CVPR 2011 Tutorial | http://cvrc.ece.utexas.edu/mryoo/cvpr2011tutorial/ |
| Tutorial | Structured Prediction | Structured Prediction and Learning in Computer Vision | S. Nowozin and C. Lampert, CVPR 2011 Tutorial | http://www.nowozin.net/sebastian/cvpr2011tutorial/ |
| Tutorial | Action Recognition | Statistical and Structural Recognition of Human Actions | Ivan Laptev and Greg Mori, ECCV 2010 Tutorial | https://sites.google.com/site/humanactionstutorialeccv10/ |
| Tutorial | Computational Symmetry | Computational Symmetry: Past, Current, Future | Yanxi Liu, ECCV 2010 Tutorial | http://vision.cse.psu.edu/research/symmComp/index.shtml |
| Tutorial | Matlab | Matlab Tutorial | David Kriegman and Serge Belongie | http://www.cs.unc.edu/~lazebnik/spring10/matlab.intro.html |
| Tutorial | Matlab | Writing Fast MATLAB Code | Pascal Getreuer, Yale University | http://www.mathworks.com/matlabcentral/fileexchange/5685 |
| Tutorial | Spectral Clustering | A Tutorial on Spectral Clustering | Ulrike von Luxburg, Max Planck Institute for Biological Cybernetics | http://web.mit.edu/~wingated/www/introductions/tutorial_on_spectral_clustering.pdf |
| Tutorial | Feature Learning, Image Classification | Feature Learning for Image Classification | Kai Yu and Andrew Ng, ECCV 2010 Tutorial | http://ufldl.stanford.edu/eccv10-tutorial/ |
| Tutorial | Shape Analysis, Diffusion Geometry | Diffusion Geometry Methods in Shape Analysis | A. Brontein and M. Bronstein, ECCV 2010 Tutorial | http://tosca.cs.technion.ac.il/book/course_eccv10.html |
| Tutorial | Graphical Models | Graphical Models, Exponential Families, and Variational Inference | Martin J. Wainwright and Michael I. Jordan, University of California at Berkeley | http://www.eecs.berkeley.edu/~wainwrig/Papers/WaiJor08_FTML.pdf |
| Tutorial | Color Image Processing | Color image understanding: from acquisition to high-level image understanding | Theo Gevers, Keigo Hirakawa, Joost van de Weijer, ICCV 2011 Tutorial | http://www.cat.uab.cat/~joost/tutorial_iccv.html |
| Tutorial | Structure from motion | Nonrigid Structure from Motion | Y. Sheikh and Sohaib Khan, ECCV 2010 Tutorial | http://www.cs.cmu.edu/~yaser/ECCV2010Tutorial.html |
| Tutorial | Expectation Maximization | A Gentle Tutorial of the EM Algorithmand its Application to ParameterEstimation for Gaussian Mixture andHidden Markov Models | Jeff A. Bilmes, University of California at Berkeley | http://crow.ee.washington.edu/people/bulyko/papers/em.pdf |
| Tutorial | Decision Forests | Decision forests for classification, regression, clustering and density estimation | A. Criminisi, J. Shotton and E. Konukoglu, ICCV 2011 Tutorial | http://research.microsoft.com/en-us/groups/vision/decisionforests.aspx |
| Tutorial | 3D point cloud processing | 3D point cloud processing: PCL (Point Cloud Library) | R. Rusu, S. Holzer, M. Dixon, V. Rabaud, ICCV 2011 Tutorial | http://www.pointclouds.org/media/iccv2011.html |
| Tutorial | Image Registration | Tools and Methods for Image Registration | Brown, G. Carneiro, A. A. Farag, E. Hancock, A. A. Goshtasby (Organizer), J. Matas, J.M. Morel, N. S. Netanyahu, F. Sur, and G. Yu, CVPR 2011 Tutorial | http://www.imgfsr.com/CVPR2011/Tutorial6/ |
| Tutorial | Non-rigid registration | Non-rigid registration and reconstruction | Alessio Del Bue, Lourdes Agapito, Adrien Bartoli, ICCV 2011 Tutorial | http://www.isr.ist.utl.pt/~adb/tutorial/ |
| Tutorial | Variational Calculus | Variational Methods in Computer Vision | D. Cremers, B. Goldlücke, T. Pock, ECCV 2010 Tutorial | http://cvpr.cs.tum.edu/tutorials/eccv2010 |
| Tutorial | Distance Metric Learning | Distance Functions and Metric Learning | M. Werman, O. Pele and B. Kulis, ECCV 2010 Tutorial | http://www.cs.huji.ac.il/~ofirpele/DFML_ECCV2010_tutorial/ |
| Tutorial | Feature Extraction | Image and Video Description with Local Binary Pattern Variants | M. Pietikainen and J. Heikkila, CVPR 2011 Tutorial | http://www.ee.oulu.fi/research/imag/mvg/files/pdf/CVPR-tutorial-final.pdf |
| Tutorial | Game Theory | Game Theory in Computer Vision and Pattern Recognition | Marcello Pelillo and Andrea Torsello, CVPR 2011 Tutorial | http://www.dsi.unive.it/~atorsell/cvpr2011tutorial/ |
| Tutorial | Computational Imaging | Fcam: an architecture and API for computational cameras | Kari Pulli, Andrew Adams, Timo Ahonen, Marius Tico, ICCV 2011 Tutorial | http://fcam.garage.maemo.org/iccv2011.html |
