state-of-the-art implementations related to visual recognition and search

http://rogerioferis.com/VisualRecognitionAndSearch2014/Resources.html

Source Code

Non-exhaustive list of state-of-the-art implementations related to visual recognition and search. There is no warranty for the source code links below – use them at your own risk!

Feature Detection and Description

General Libraries: 

VLFeat – Implementation of various feature descriptors (including SIFT, HOG, and LBP) and covariant feature detectors (including DoG, Hessian, Harris
Laplace, Hessian Laplace, Multiscale Hessian, Multiscale Harris). Easy-to-use Matlab interface. SeeModern
features: Software – Slides providing a demonstration of VLFeat and also links to other software. Check also VLFeat hands-on
session training

OpenCV – Various implementations of modern feature detectors and descriptors (SIFT, SURF, FAST, BRIEF, ORB, FREAK, etc.)

Fast Keypoint Detectors for Real-time Applications: 

FAST – High-speed corner detector implementation for a wide variety of platforms

AGAST – Even faster than the FAST corner detector. A multi-scale version of this method is used for the BRISK descriptor (ECCV
2010).

Binary Descriptors for Real-Time Applications: 

BRIEF – C++ code for a fast and accurate interest point descriptor (not invariant to rotations and scale) (ECCV 2010)

ORB – OpenCV implementation of the Oriented-Brief (ORB) descriptor (invariant to rotations,
but not scale)

BRISK – Efficient Binary descriptor invariant to rotations and scale. It includes a Matlab mex interface. (ICCV 2011)

FREAK – Faster than BRISK (invariant to rotations and scale) (CVPR 2012)

SIFT and SURF Implementations: 

SIFT: VLFeat, OpenCV, Original
code by David Lowe, GPU implementation, OpenSIFT

SURF: Herbert Bay’s code, OpenCV, GPU-SURF

Other Local Feature Detectors and Descriptors: 

VGG Affine Covariant features – Oxford code for various affine covariant feature detectors and descriptors.

LIOP descriptor – Source code for the Local Intensity order Pattern (LIOP) descriptor (ICCV 2011).

Local Symmetry Features – Source code for matching of local symmetry features under large variations in lighting, age, and
rendering style (CVPR 2012).

Global Image Descriptors: 

GIST – Matlab code for the GIST descriptor

CENTRIST – Global visual descriptor for scene categorization and object detection (PAMI 2011)

Feature Coding and Pooling 

VGG Feature Encoding Toolkit – Source code for various state-of-the-art feature encoding methods – including
Standard hard encoding, Kernel codebook encoding, Locality-constrained linear encoding, and Fisher kernel encoding.

Spatial Pyramid Matching – Source code for feature pooling based on spatial pyramid matching (widely used for image classification)

Convolutional Nets and Deep Learning 

Caffe – Fast C++ implementation of deep convolutional networks (GPU / CPU / ImageNet 2013 demonstration).

OverFeat – C++ library for integrated classification and localization of objects.

EBLearn – C++ Library for Energy-Based Learning. It includes several demos and step-by-step instructions to train classifiers based on
convolutional neural networks.

Torch7 – Provides a matlab-like environment for state-of-the-art machine learning algorithms, including a fast implementation of convolutional neural
networks.

Deep Learning - Various links for deep learning software.

Facial Feature Detection and Tracking 

IntraFace – Very accurate detection and tracking of facial features (C++/Matlab API).

Part-Based Models 

Deformable Part-based Detector – Library provided by the authors of the original paper (state-of-the-art in PASCAL VOC detection
task)

Efficient Deformable Part-Based Detector – Branch-and-Bound implementation for a deformable part-based detector.

Accelerated Deformable Part Model – Efficient implementation of a method that achieves the exact same performance of deformable
part-based detectors but with significant acceleration (ECCV 2012).

Coarse-to-Fine Deformable Part Model – Fast approach for deformable object detection (CVPR 2011).

Poselets – C++ and Matlab versions for object detection based on poselets.

Part-based Face Detector and Pose Estimation – Implementation of a unified approach for face detection, pose estimation, and landmark
localization (CVPR 2012).

Attributes and Semantic Features 

Relative Attributes – Modified implementation of RankSVM to train Relative Attributes (ICCV 2011).

Object Bank – Implementation of object bank semantic features (NIPS 2010). See also ActionBank

Classemes, Picodes, and Meta-class features – Software for extracting high-level image descriptors
(ECCV 2010, NIPS 2011, CVPR 2012).

Large-Scale Learning 

Additive Kernels – Source code for fast additive kernel SVM classifiers (PAMI 2013).

LIBLINEAR – Library for large-scale linear SVM classification.

VLFeat – Implementation for Pegasos SVM and Homogeneous Kernel map.

Fast Indexing and Image Retrieval 

FLANN – Library for performing fast approximate nearest neighbor.

Kernelized LSH – Source code for Kernelized Locality-Sensitive Hashing (ICCV 2009).

ITQ Binary codes – Code for generation of small binary codes using Iterative Quantization and other baselines such as Locality-Sensitive-Hashing
(CVPR 2011).

INRIA Image Retrieval – Efficient code for state-of-the-art large-scale image retrieval (CVPR 2011).

Object Detection 

See Part-based Models and Convolutional
Nets above.

Pedestrian Detection at 100fps – Very fast and accurate pedestrian detector (CVPR 2012).

Caltech Pedestrian Detection Benchmark – Excellent resource for pedestrian detection, with various links
for state-of-the-art implementations.

OpenCV – Enhanced implementation of Viola&Jones real-time object
detector, with trained models for face detection.

Efficient Subwindow Search – Source code for branch-and-bound optimization for efficient object localization (CVPR
2008).

3D Recognition 

Point-Cloud Library – Library for 3D image and point cloud processing.

Action Recognition 

ActionBank – Source code for action recognition based on the ActionBank representation (CVPR 2012).

STIP Features – software for computing space-time interest point descriptors

Independent Subspace Analysis – Look for Stacked ISA for Videos (CVPR 2011)

Velocity Histories of Tracked Keypoints - C++ code for activity recognition using the velocity histories of tracked keypoints
(ICCV 2009)

Datasets

Attributes 

Animals with Attributes – 30,475 images of 50 animals classes with 6 pre-extracted feature representations for each image.

aYahoo and aPascal – Attribute annotations for images collected from Yahoo and Pascal VOC 2008.

FaceTracer – 15,000 faces annotated with 10 attributes and fiducial points.

PubFig – 58,797 face images of 200 people with 73 attribute classifier outputs.

LFW – 13,233 face images of 5,749 people with 73 attribute classifier outputs.

Human Attributes – 8,000 people with annotated attributes. Check also this link for
another dataset of human attributes.

SUN Attribute Database – Large-scale scene attribute database with a taxonomy of 102 attributes.

ImageNet Attributes – Variety of attribute labels for the ImageNet dataset.

Relative attributes – Data for OSR and a subset of PubFig datasets. Check also this link for
the WhittleSearch data.

Attribute Discovery Dataset – Images of shopping categories associated with textual descriptions.

Fine-grained Visual Categorization 

Caltech-UCSD Birds Dataset – Hundreds of bird categories with annotated parts and attributes.

Stanford Dogs Dataset – 20,000 images of 120 breeds of dogs from around the world.

Oxford-IIIT Pet Dataset – 37 category pet dataset with roughly 200 images for each class. Pixel level trimap segmentation is
included.

Leeds Butterfly Dataset – 832 images of 10 species of butterflies.

Oxford Flower Dataset – Hundreds of flower categories.

Face Detection 

FDDB – UMass face detection dataset and benchmark (5,000+ faces)

CMU/MIT – Classical face detection dataset.

Face Recognition 

Face Recognition Homepage – Large collection of face recognition datasets.

LFW – UMass unconstrained face recognition dataset (13,000+ face images).

NIST Face Homepage – includes face recognition grand challenge (FRGC), vendor tests (FRVT) and others.

CMU Multi-PIE – contains more than 750,000 images of 337 people, with 15 different views and 19 lighting conditions.

FERET – Classical face recognition dataset.

Deng Cai’s face dataset in Matlab Format – Easy to use if you want play with simple face datasets including Yale,
ORL, PIE, and Extended Yale B.

SCFace – Low-resolution face dataset captured from surveillance cameras.

Handwritten Digits 

MNIST – large dataset containing a training set of 60,000 examples, and a test set of 10,000 examples.

Pedestrian Detection

Caltech Pedestrian Detection Benchmark – 10 hours of video taken from a vehicle,350K bounding boxes for
about 2.3K unique pedestrians.

INRIA Person Dataset – Currently one of the most popular pedestrian detection datasets.

ETH Pedestrian Dataset – Urban dataset captured from a stereo rig mounted on a stroller.

TUD-Brussels Pedestrian Dataset – Dataset with image pairs recorded in an crowded urban setting with an onboard camera.

PASCAL Human Detection – One of 20 categories in PASCAL VOC detection challenges.

USC Pedestrian Dataset – Small dataset captured from surveillance cameras.

Generic Object Recognition 

ImageNet – Currently the largest visual recognition dataset in terms of number of categories and images.

Tiny Images – 80 million 32x32 low resolution images.

Pascal VOC – One of the most influential visual recognition datasets.

Caltech 101 / Caltech
256 – Popular image datasets containing 101 and 256 object categories, respectively.

MIT LabelMe – Online annotation tool for building computer vision databases.

Scene Recognition

MIT SUN Dataset – MIT scene understanding dataset.

UIUC Fifteen Scene Categories – Dataset of 15 natural scene categories.

Feature Detection and Description 

VGG Affine Dataset – Widely used dataset for measuring performance of feature detection and description. CheckVLBenchmarks for
an evaluation framework.

Action Recognition

Benchmarking Activity Recognition – CVPR 2012 tutorial covering various datasets
for action recognition.

RGBD Recognition 

RGB-D Object Dataset – Dataset containing 300 common household objects