Disparity Estimation
52 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.
Benchmarks
These leaderboards are used to track progress in Disparity Estimation
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FlyingThings3D
Middlebury 2014
IRS
Dynamic Replica
Latest papers
CosPGD: a unified white-box adversarial attack for pixel-wise prediction tasks
shashankskagnihotri/cospgd
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Further, we set a new benchmark for adversarial attacks on optical flow, and image restoration displaying the ability to extend to any pixel-wise prediction task.
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
hk-shi/bidirectional-semisupervised-dual-branch-cnn
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The learned knowledge flows across branches along two directions: a cross direction (disparity guides distribution in ACS) and a parallel direction (disparity guides disparity in APS).
Stereoscopic Universal Perturbations across Different Architectures and Datasets
alexklwong/stereoscopic-universal-perturbations
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CVPR 2022
We study the effect of adversarial perturbations of images on deep stereo matching networks for the disparity estimation task.
TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation
cogsys-tuebingen/tristereonet
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Stereo vision is an effective technique for depth estimation with broad applicability in autonomous urban and highway driving.
Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception
We provide a SHEF dataset targeted at evaluating disparity estimation algorithms and introduce a stereo disparity estimation algorithm that uses edge information extracted from the event stream correlated with the edge detected in the frame data.
MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching
cogsys-tuebingen/mobilestereonet
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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.
Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation
Besides the cross-view information exploitation in the low-resolution (LR) space, HR representations produced by the SR process are utilized to perform HR disparity estimation with higher accuracy, through which the HR features can be aggregated to generate a finer SR result.
SBEVNet: End-to-End Deep Stereo Layout Estimation
divamgupta/sbevnet-stereo-layout-estimation
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Instead, the learning of a good internal bird's eye view feature representation is effective for layout estimation.
CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching
In this paper, we propose CFNet, a Cascade and Fused cost volume based network to improve the robustness of the stereo matching network.
SMD-Nets: Stereo Mixture Density Networks
fabiotosi92/SMD-Nets
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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.
