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 26–50 of 162 papers

TitleStatusHype
Global Occlusion-Aware Transformer for Robust Stereo MatchingCode1
An evaluation of Deep Learning based stereo dense matching dataset shift from aerial images and a large scale stereo datasetCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
S3Net: Innovating Stereo Matching and Semantic Segmentation with a Single-Branch Semantic Stereo Network in Satellite Epipolar ImageryCode1
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel SupervisionsCode1
Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity EstimationCode1
Superpixel Segmentation with Fully Convolutional NetworksCode1
Attention-based View Selection Networks for Light-field Disparity EstimationCode1
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity EstimationCode1
3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric PriorsCode1
On the Over-Smoothing Problem of CNN Based Disparity EstimationCode0
A hybrid algorithm for disparity calculation from sparse disparity estimates based on stereo visionCode0
Road surface 3d reconstruction based on dense subpixel disparity map estimationCode0
Color Agnostic Cross-Spectral Disparity EstimationCode0
Understanding and Robustifying Differentiable Architecture SearchCode0
Multispectral Snapshot Image Registration Using Learned Cross Spectral Disparity Estimation and a Deep Guided Occlusion Reconstruction NetworkCode0
Movement-induced Priors for Deep StereoCode0
CBMV: A Coalesced Bidirectional Matching Volume for Disparity EstimationCode0
A Decomposition Model for Stereo MatchingCode0
Multi-View Stereo by Temporal Nonparametric FusionCode0
DispBench: Benchmarking Disparity Estimation to Synthetic CorruptionsCode0
Learning for Disparity Estimation through Feature ConstancyCode0
Learning on the Edge: Explicit Boundary Handling in CNNsCode0
BidNet: Binocular Image Dehazing Without Explicit Disparity EstimationCode0
Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression TasksCode0
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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