Disparity Estimation
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Greatest papers with code
Learning for Disparity Estimation through Feature Constancy
CVPR 2018
• JiaRenChang/PSMNet
• 
The second part performs matching cost calculation, matching cost aggregation and disparity calculation to estimate the initial disparity using shared features.
Embedded real-time stereo estimation via Semi-Global Matching on the GPU
Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles.
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch
ICCV 2019
• uber-research/DeepPruner
•
Our goal is to significantly speed up the runtime of current state-of-the-art stereo algorithms to enable real-time inference.
AUTONOMOUS DRIVING DISPARITY ESTIMATION IMAGE RECONSTRUCTION STEREO MATCHING
Understanding and Robustifying Differentiable Architecture Search
Differentiable Architecture Search (DARTS) has attracted a lot of attention due to its simplicity and small search costs achieved by a continuous relaxation and an approximation of the resulting bi-level optimization problem.
DISPARITY ESTIMATION IMAGE CLASSIFICATION LANGUAGE MODELLING
Fast Disparity Estimation using Dense Networks
Disparity estimation is a difficult problem in stereo vision because the correspondence technique fails in images with textureless and repetitive regions.
CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation
The success of these methods is due to the availability of training data with ground truth; training learning-based systems on these datasets has allowed them to surpass the accuracy of conventional approaches based on heuristics and assumptions.
Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching
• DeepMotionAIResearch/DenseMatchingBenchmark
•
However, disparity is just a byproduct of a matching process modeled by cost volume, while indirectly learning cost volume driven by disparity regression is prone to overfitting since the cost volume is under constrained.
Understanding and Robustifying Differentiable Architecture Search
ICLR 2020
• MetaAnonym/RobustDARTS
•
Differentiable Architecture Search (DARTS) has attracted a lot of attention due to its simplicity and small search costs achieved by a continuous relaxation and an approximation of the resulting bi-level optimization problem.
DISPARITY ESTIMATION IMAGE CLASSIFICATION LANGUAGE MODELLING
Detect, Replace, Refine: Deep Structured Prediction For Pixel Wise Labeling
Instead, we propose a generic architecture that decomposes the label improvement task to three steps: 1) detecting the initial label estimates that are incorrect, 2) replacing the incorrect labels with new ones, and finally 3) refining the renewed labels by predicting residual corrections w. r. t.
DISPARITY ESTIMATION STEREO MATCHING STEREO MATCHING HAND STRUCTURED PREDICTION
SENSE: a Shared Encoder Network for Scene-flow Estimation
We introduce a compact network for holistic scene flow estimation, called SENSE, which shares common encoder features among four closely-related tasks: optical flow estimation, disparity estimation from stereo, occlusion estimation, and semantic segmentation.
DISPARITY ESTIMATION OPTICAL FLOW ESTIMATION SCENE FLOW ESTIMATION SEMANTIC SEGMENTATION