Disparity Estimation

47 papers with code • 4 benchmarks • 4 datasets

The Disparity Estimation is the task of finding the pixels in the multiscopic views that correspond to the same 3D point in the scene.

Most implemented papers

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


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

CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching

gallenszl/CFNet CVPR 2021

In this paper, we propose CFNet, a Cascade and Fused cost volume based network to improve the robustness of the stereo matching network.

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

cogsys-tuebingen/mobilestereonet 22 Aug 2021

Depending on the dimension of cost volume, we design a 2D and a 3D model with encoder-decoders built from 2D and 3D convolutions, respectively.

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.

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.

PCW-Net: Pyramid Combination and Warping Cost Volume for Stereo Matching

gallenszl/pcwnet 23 Jun 2020

First, we construct combination volumes on the upper levels of the pyramid and develop a cost volume fusion module to integrate them for initial disparity estimation.

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.

Blur aware metric depth estimation with multi-focus plenoptic cameras

comsee-research/libpleno 8 Aug 2023

A method to calibrate the inverse model is then proposed.

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.

Detect, Replace, Refine: Deep Structured Prediction For Pixel Wise Labeling

gidariss/DRR_struct_pred CVPR 2017

Instead, we propose a generic architecture that decomposes the label improvement task to three steps: 1) detecting the initial label estimates that are incorrect, 2) replacing the incorrect labels with new ones, and finally 3) refining the renewed labels by predicting residual corrections w. r. t.