SOTAVerified

Disparity Estimation

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

Papers

Showing 1120 of 162 papers

TitleStatusHype
FADNet: A Fast and Accurate Network for Disparity EstimationCode1
Fast Light-Field Disparity Estimation With Multi-Disparity-Scale Cost AggregationCode1
An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo datasetCode1
CFNet: Cascade and Fused Cost Volume for Robust Stereo MatchingCode1
3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric PriorsCode1
Attention-based View Selection Networks for Light-field Disparity EstimationCode1
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow EstimationCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel SupervisionsCode1
Blur aware metric depth estimation with multi-focus plenoptic camerasCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Two-stream CNN+CLSTMBadPix(0.01)62.05Unverified
#ModelMetricClaimedVerifiedStatus
1Two-stream CNN+CLSTMBadPix(0.01)53.3Unverified
#ModelMetricClaimedVerifiedStatus
1Two-stream CNN+CLSTMBadPix(0.01)74.77Unverified
#ModelMetricClaimedVerifiedStatus
1Two-stream CNN+CLSTMBadPix(0.01)17.75Unverified