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 51–75 of 162 papers

TitleStatusHype
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection—0
EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual—0
Analytic Signal Phase in N-D by Linear Symmetry Tensor--fingerprint modeling—0
End-to-End Learning of Multi-scale Convolutional Neural Network for Stereo Matching—0
Light Field Super-Resolution Via Graph-Based Regularization—0
Low Compute and Fully Parallel Computer Vision With HashMatch—0
AMNet: Deep Atrous Multiscale Stereo Disparity Estimation Networks—0
Eye2Eye: A Simple Approach for Monocular-to-Stereo Video Synthesis—0
Disparity estimation for fisheye images with an application to intermediate view synthesis—0
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks—0
Fast Disparity Estimation from a Single Compressed Light Field Measurement—0
Deep 3D-Zoom Net: Unsupervised Learning of Photo-Realistic 3D-Zoom—0
Blur-Aware Disparity Estimation From Defocus Stereo Images—0
Learning Light Field Reconstruction from a Single Coded Image—0
Disparity-Aware Domain Adaptation in Stereo Image Restoration—0
Disentangling Light Fields for Super-Resolution and Disparity Estimation—0
All-directional Disparity Estimation for Real-world QPD Images—0
DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning—0
ADCPNet: Adaptive Disparity Candidates Prediction Network for Efficient Real-Time Stereo Matching—0
Learning based Deep Disentangling Light Field Reconstruction and Disparity Estimation Application—0
Left-Right Comparative Recurrent Model for Stereo Matching—0
Bayesian Learning for Disparity Map Refinement for Semi-Dense Active Stereo Vision—0
Investigating Spherical Epipolar Rectification for Multi-View Stereo 3D Reconstruction—0
IFAST: Weakly Supervised Interpretable Face Anti-spoofing from Single-shot Binocular NIR Images—0
Hyperspectral Light Field Stereo Matching—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