Browse State-of-the-Art › Hand Gesture Recognition

Hand Gesture Recognition

53 papers with code · 18 benchmarks · 16 datasets archive 2025-07-28

Computer Vision

Hand gesture recognition (HGR) is a subarea of Computer Vision where the focus is on classifying a video or image containing a dynamic or static, respectively, hand gesture. In the static case, gestures are also generally called poses. HGR can also be performed with point cloud or joint hand data.

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

18 leaderboard tables shown for this task, 18 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. 10 shown of 18 until expanded.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
DHG-14 (13 rows) e2eET Real-Time Hand Gesture Recognition: Integrating Skeleton-Based... code — Compare
DHG-28 (9 rows) DSTSA-GCN DSTSA-GCN: Advancing Skeleton-Based Gesture Recognition with... code — Compare
NVGesture (5 rows) De+Recouple Decoupling and Recoupling Spatiotemporal Representation for... code — Compare
EgoGesture (4 rows) ResNeXt-101 Real-time Hand Gesture Detection and Classification Using... code — Compare
SHREC 2017 (4 rows) e2eET Real-Time Hand Gesture Recognition: Integrating Skeleton-Based... code — Compare
ChaLearn val (3 rows) 8-MFFs-3f1c (5 crop) Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture... code — Compare
LSA16 (3 rows) Prototypical Networks + CNN A comparison of small sample methods for Handshape Recognition code — Compare
SHREC 2017 track on 3D Hand Gesture Recognition (3 rows) 3DCNN_VIVA_4 Compressing 3DCNNs Based on Tensor Train Decomposition — — Compare
VIVA Hand Gestures Dataset (3 rows) MTUT Improving the Performance of Unimodal Dynamic Hand-Gesture... code — Compare
Cambridge (2 rows) Key Frames + Feature Fusion Fast and Robust Dynamic Hand Gesture Recognition via Key Frames... code — Compare
Jester test (2 rows) DRX3D Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture... code — Compare
RWTH-PHOENIX Handshapes dev set (2 rows) DenseNet A comparison of small sample methods for Handshape Recognition code — Compare
BUAA (1 row) F-BGRU Deep Fisher Discriminant Learning for Mobile Hand Gesture Recognition code — Compare
ChaLean test (1 row) 8-MFFs-3f1c Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture... code — Compare
Jester val (1 row) 8-MFFs-3f1c (5 crop) Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture... code — Compare
MGB (1 row) F-BLSTM Deep Fisher Discriminant Learning for Mobile Hand Gesture Recognition code — Compare
Northwestern University (1 row) Key Frames + Feature Fusion Fast and Robust Dynamic Hand Gesture Recognition via Key Frames... code — Compare
SmartWatch (1 row) F-BGRU Deep Fisher Discriminant Learning for Mobile Hand Gesture Recognition code — 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

16 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

30 shown of 53 papers with code (198 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.

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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