Awesome

Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks

<img src="figure/figure.png" width="60%" height="50%">

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.

Dependencies：

Python 3.6
PyTorch 1.7.0
torchvision 0.3.0
SceneFlow
KITTI stereo 2015
KITTI stereo 2012

Training on SceneFlow

python train.py --data_path (your Scene Flow data folder)

Finetuning on KITTI

python KITTI_ft.py --data_path (your KITTI training data folder) --load_path (the path of the model trained on SceneFlow)

Pretrained Models