快速去阴影--Fast Shadow Detection from a Single Image Using a Patched Convolutional Neural Network

Fast Shadow Detection from a Single Image Using a Patched Convolutional Neural Network

https://arxiv.org/abs/1709.09283

本文主要解决快速去阴影问题，这里使用的策略是 SVM+CNN



A. Computing Shadow Prior

首先使用 mean shift 算法对输入图像进行过分割，得到 segment, 对每个 segment 我们提取其 color and texture features 信息输入 SVM 得到 shadow prior 就是 the log likelihood output of this trained classifier

B. Training Patched-CNN with the Shadow Prior

基于文献【17】，我们使用一个 Patched-CNN 来 predict shadow，其输入是 shadow prior (P) 和对应的 RGB image，输出是 shadow probability map of the patch

C. Edge Refinement of Super-Pixel Labels

上一步主要是 region， 阴影的边界 的 prediction 比较差，所以我们这里 process the edge pixels between the regions by patched-CNN once again，We only process those pixels that are on edges between the segments

Experiments









速度还是比较慢啊！