Browse State-of-the-Art › Stereo Disparity Estimation
Stereo Disparity Estimation
19 papers with code · 3 benchmarks · 7 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
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| Scene Flow (7 rows) | AANet | AANet: Adaptive Aggregation Network for Efficient Stereo Matching | code | Syntology ran 9 of 14 samples · 5 unverified | Compare |
| KITTI 2015 (2 rows) | MoCha-Stereo | MoCha-Stereo: Motif Channel Attention Network for Stereo Matching | code | Syntology ran 16 of 17 samples · 1 unverified | Compare |
| Middlebury 2014 (2 rows) | MoCha-V2 | MoCha-Stereo: Motif Channel Attention Network for Stereo Matching | code | Syntology ran 16 of 17 samples · 1 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
7 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
19 shown of 19 papers with code (29 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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23 Jul 2020 9 repositories listed Syntology ran 1 of 5 samples · 4 unverifiedContrary 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…
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3 Mar 2023 2 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 4 pointer-only (licence)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…
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10 Apr 2024 1 repository listed Syntology ran 16 of 17 samples · 1 unverifiedIn 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…
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17 Mar 2024 1 repository listed Syntology ran 12 of 13 samples · 1 unverifiedStereo matching is a core task for many computer vision and robotics applications.
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19 Feb 2024 1 repository listedTo address this challenge, we propose a method for generating ground-truth disparity maps directly from Light Detection and Ranging (LiDAR) and images to produce a large and diverse dataset for six aerial datasets…
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1 Jun 2023 1 repository listedComputer vision systems that are deployed in safety-critical applications need to quantify their output uncertainty.
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22 Apr 2023 1 repository listedTo address the aforementioned challenges, this paper proposes a novel approach where a high-resolution convolutional neural network is used to better capture relationships between the two spectra.
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11 Oct 2021 1 repository listedWe provide a SHEF dataset targeted at evaluating disparity estimation algorithms and introduce a stereo disparity estimation algorithm that uses edge information extracted from the event stream correlated with the edge…
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15 Sep 2021 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)We introduce RAFT-Stereo, a new deep architecture for rectified stereo based on the optical flow network RAFT.
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26 Oct 2020 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classification and semantic segmentation.
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18 Oct 2020 1 repository listedWe propose a method for fusing stereo disparity estimation with movement-induced prior information.
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21 Sep 2020 1 repository listedWe study the effect of adversarial perturbations of images on the estimates of disparity by deep learning models trained for stereo.
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11 Aug 2020 1 repository listedFinally, a matchability-aware disparity refinement is introduced to improve the depth inference in weakly matchable regions.
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6 Jul 2020 1 repository listed Syntology ran 2 of 9 samples · 7 unverifiedExisting approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values.
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20 Apr 2020 1 repository listed Syntology ran 9 of 14 samples · 5 unverifiedDespite the remarkable progress made by learning based stereo matching algorithms, one key challenge remains unsolved.
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21 Jan 2020 1 repository listedComplete disparity maps are reconstructed from boundaries' disparities.
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20 Jan 2020 1 repository listedIn 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.
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16 Jul 2018 1 repository listedIn this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems.
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1 Jan 2018 1 repository listedOur 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.
Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections