Browse State-of-the-Art › Grasp Contact Prediction
Grasp Contact Prediction
4 papers with code · 2 benchmarks · 5 datasets archive 2025-07-28
Predict contact between object and hand (human or robot).
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 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 |
|---|---|---|---|---|---|
| ContactDB (4 rows) | DiverseNet-VoxNet | ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging | code | — | Compare |
| ContactPose (1 row) | MLP + mesh-features | ContactPose: A Dataset of Grasps with Object Contact and Hand Pose | code | Syntology ran 3 of 4 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
5 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
4 shown of 4 papers with code (4 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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25 Aug 2020 2 repositories listedTraining computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, detailed contact information, hand pose and shape, and the 3D body motion over time.
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19 Jul 2020 2 repositories listed Syntology ran 3 of 4 samples · 1 unverifiedWe introduce ContactPose, the first dataset of hand-object contact paired with hand pose, object pose, and RGB-D images.
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15 Apr 2019 2 repositories listedWe present ContactDB, a novel dataset of contact maps for household objects that captures the rich hand-object contact that occurs during grasping, enabled by use of a thermal camera.
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19 Sep 2021 1 repository listedThis work proposes a framework to learn task-relevant grasping for industrial objects without the need of time-consuming real-world data collection or manual annotation.
Syntology lines on 1 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.
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