Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Contributions
A novel pairwise feature LSP to extract structural information, which is beneficial for accurate matching especially when the illumination of the image pair is imbalanced
A novel disparity refinement method CSR (or DSR to save memory) to deal with outliers that are difficult to match, e.g. disparity discontinuities and occluded regions.
This project is a re-implementation of MASTER: Multi-Aspect Non-local Network for Scene Text Recognition by MMOCR,which is an open-source toolbox based on PyTorch. The overall architecture will be sh
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well i