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https://github.com/uber-research/DeepPruner

DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch (ICCV 2019)
https://github.com/uber-research/DeepPruner

iccv2019 patchmatch pytorch real-time stereo-matching stereo-vision

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

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README

        

# DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch

This repository releases code for our paper [DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch](https://arxiv.org/abs/1909.05845).

##### Table of Contents
[DeepPruner](#DeepPruner)
[Differentiable Patch Match](#DifferentiablePatchMatch)
[Requirements (Major Dependencies)](#Requirements)
[Citation](#Citation)


### **DeepPruner**

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



![](readme_images/DeepPruner.png)



+ Results/ Metrics:

+ [**KITTI**](http://www.cvlibs.net/datasets/kitti/eval_scene_flow.php?benchmark=stereo): **Results competitive to SOTA, while being real-time (8x faster than SOTA). SOTA among published real-time algorithms**.


![](readme_images/KITTI_test_set.png)
![](readme_images/CRP.png)
![](readme_images/uncertainty_vis.png)


+ [**ETH3D**](https://www.eth3d.net/low_res_two_view?mask=all&metric=bad-2-0): **SOTA among all ROB entries**.

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







+ [**Robust Vision Challenge**](http://www.robustvision.net/index.php): **Overall ranking 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.](https://gfx.cs.princeton.edu/pubs/Barnes_2010_TGP/index.php))



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 , Shenlong Wang , Wei-Chiu Ma