Stereo Disparity Estimation
18 papers with code • 3 benchmarks • 6 datasets
Benchmarks
These leaderboards are used to track progress in Stereo Disparity Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
Libraries
Use these libraries to find Stereo Disparity Estimation models and implementations
KITTI
Middlebury 2014
Spring
SERV-CT
L1BSR
Most implemented papers
HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching
google-research/google-research
•
•
CVPR 2021
Contrary to many recent neural network approaches that operate on a full cost volume and rely on 3D convolutions, our approach does not explicitly build a volume and instead relies on a fast multi-resolution initialization step, differentiable 2D geometric propagation and warping mechanisms to infer disparity hypotheses.
Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo
While recent methods for motion and stereo estimation recover an unprecedented amount of details, such highly detailed structures are neither adequately reflected in the data of existing benchmarks nor their evaluation methodology.
MoCha-Stereo: Motif Channel Attention Network for Stereo Matching
In addition, edge variations in %potential feature channels of the reconstruction error map also affect details matching, we propose the Reconstruction Error Motif Penalty (REMP) module to further refine the full-resolution disparity estimation.
SOS: Stereo Matching in O(1) with Slanted Support Windows
Our key insight is that local smoothness can in fact be used to amortize the computation not only within initialization, but across the entire stereo pipeline.
ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems
meteorshowers/X-StereoLab
•
•
ECCV 2018
In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems.
A hybrid algorithm for disparity calculation from sparse disparity estimates based on stereo vision
In this paper, we have proposed a novel method for stereo disparity estimation by combining the existing methods of block based and region based stereo matching.
Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework
Complete disparity maps are reconstructed from boundaries' disparities.
AANet: Adaptive Aggregation Network for Efficient Stereo Matching
Despite the remarkable progress made by learning based stereo matching algorithms, one key challenge remains unsolved.
Wasserstein Distances for Stereo Disparity Estimation
Div99/W-Stereo-Disp
•
•
NeurIPS 2020
Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values.
Learning Stereo Matchability in Disparity Regression Networks
jzhangbs/DSM
•
•
Finally, a matchability-aware disparity refinement is introduced to improve the depth inference in weakly matchable regions.
