This repository releases code for our paper DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch.
DeepPruner
Differentiable Patch Match
Requirements (Major Dependencies)
Citation
An efficient "Real Time Stereo Matching" algorithm, which takes as input 2 images and outputs a disparity (or depth) map.
Results/ Metrics:
Runtime: 62ms (for DeepPruner-fast), 180ms (for DeepPruner-best)
Cuda Memory Requirements: 805MB (for DeepPruner-best)
More details in the corresponding folder README.
If you use our source code, or our paper, please consider citing the following:
@inproceedings{Duggal2019ICCV,
title = {DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch},
author = {Shivam Duggal and Shenlong Wang and Wei-Chiu Ma and Rui Hu and Raquel Urtasun},
booktitle = {ICCV},
year = {2019} }
Correspondences to Shivam Duggal shivamduggal.9507@gmail.com, Shenlong Wang slwang@cs.toronto.edu, Wei-Chiu Ma weichium@mit.edu