Disparity Estimation

29 papers with code • 4 benchmarks • 3 datasets

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Greatest papers with code

Learning for Disparity Estimation through Feature Constancy

JiaRenChang/PSMNet CVPR 2018

The second part performs matching cost calculation, matching cost aggregation and disparity calculation to estimate the initial disparity using shared features.

Disparity Estimation Stereo Matching +1

Embedded real-time stereo estimation via Semi-Global Matching on the GPU

dhernandez0/sgm 13 Oct 2016

Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles.

Autonomous Vehicles Disparity Estimation

Superpixel Segmentation with Fully Convolutional Networks

fuy34/superpixel_fcn CVPR 2020

In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing.

Disparity Estimation Stereo Matching

YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection

Owen-Liuyuxuan/visualDet3D 17 Mar 2021

Object detection in 3D with stereo cameras is an important problem in computer vision, and is particularly crucial in low-cost autonomous mobile robots without LiDARs.

3D Object Detection Disparity Estimation +1

Understanding and Robustifying Differentiable Architecture Search

automl/RobustDARTS ICLR 2020

Differentiable Architecture Search (DARTS) has attracted a lot of attention due to its simplicity and small search costs achieved by a continuous relaxation and an approximation of the resulting bi-level optimization problem.

Disparity Estimation Image Classification +1

Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching

DeepMotionAIResearch/DenseMatchingBenchmark 9 Sep 2019

However, disparity is just a byproduct of a matching process modeled by cost volume, while indirectly learning cost volume driven by disparity regression is prone to overfitting since the cost volume is under constrained.

Disparity Estimation Stereo Matching +1

FADNet: A Fast and Accurate Network for Disparity Estimation

HKBU-HPML/FADNet 24 Mar 2020

Deep neural networks (DNNs) have achieved great success in the area of computer vision.

Disparity Estimation Stereo Matching

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

HKBU-HPML/FADNet CVPR 2016

By combining a flow and disparity estimation network and training it jointly, we demonstrate the first scene flow estimation with a convolutional network.

Disparity Estimation Optical Flow Estimation +1

SMD-Nets: Stereo Mixture Density Networks

fabiotosi92/SMD-Nets CVPR 2021

Despite stereo matching accuracy has greatly improved by deep learning in the last few years, recovering sharp boundaries and high-resolution outputs efficiently remains challenging.

Disparity Estimation Stereo Matching