Skip to content

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch (ICCV 2019)

License

Notifications You must be signed in to change notification settings

uber-research/DeepPruner

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

13 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch

This repository releases code for our paper DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch.

Table of Contents

DeepPruner
Differentiable Patch Match
Requirements (Major Dependencies)
Citation

DeepPruner

  • An efficient "Real Time Stereo Matching" algorithm, which takes as input 2 images and outputs a disparity (or depth) map.

  • Results/ Metrics:

    • KITTI: Results competitive to SOTA, while being real-time (8x faster than SOTA). SOTA among published real-time algorithms.

    • ETH3D: SOTA among all ROB entries.

    • SceneFlow: 2nd among all published algorithms, while being 8x faster than the 1st.

    • Runtime: 62ms (for DeepPruner-fast), 180ms (for DeepPruner-best)

    • Cuda Memory Requirements: 805MB (for DeepPruner-best)

Differentiable Patch Match

  • Fast algorithm for finding dense nearest neighbor correspondences between patches of images regions. Differentiable version of the generalized Patch Match algorithm. (Barnes et al.)

More details in the corresponding folder README.

Requirements (Major Dependencies)

  • Pytorch (0.4.1+)
  • Python2.7
  • torchvision (0.2.0+)

Citation

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

About

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch (ICCV 2019)

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages