under construction ...
Stereo Matching by Deep Learning
◦Self-Supervised Learning for Stereo Matching with Self-Improving Ability
◦Unsupervised Learning of Stereo Matching
◦Pyramid Stereo Matching Network
◦Learning for Disparity Estimation through Feature Constancy
◦Deep Material-aware Cross-spectral Stereo Matching
◦SegStereo: Exploiting Semantic Information for Disparity Estimation
◦DispSegNet: Leveraging Semantics for End-to-End Learning of Disparity Estimation from Stereo Imagery
◦Group-wise Correlation Stereo Network