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

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Showing 21–30 of 162 papers

TitleStatusHype
SR-Stereo & DAPE: Stepwise Regression and Pre-trained Edges for Practical Stereo MatchingCode0
VHS: High-Resolution Iterative Stereo Matching with Visual Hull Priors—0
Multi-view Disparity Estimation Using a Novel Gradient Consistency Model—0
MoCha-Stereo: Motif Channel Attention Network for Stereo MatchingCode2
Iterative Occlusion-Aware Light Field Depth Estimation using 4D Geometrical Cues—0
Passive Snapshot Coded Aperture Dual-Pixel RGB-D Imaging—0
Digging Into Normal Incorporated Stereo MatchingCode0
An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo datasetCode1
X-maps: Direct Depth Lookup for Event-based Structured Light SystemsCode2
Left-right Discrepancy for Adversarial Attack on Stereo Networks—0
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All datasetsSintel 4D LFV - ambushfight5Sintel 4D LFV - bamboo3Sintel 4D LFV - shaman2Sintel 4D LFV - thebigfight2

Benchmark Results

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