Hand Pose Estimation
87 papers with code • 10 benchmarks • 22 datasets
Hand pose estimation is the task of finding the joints of the hand from an image or set of video frames.
( Image credit: Pose-REN )
Benchmarks
These leaderboards are used to track progress in Hand Pose Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Hand Pose Estimation models and implementationsDatasets
3DPW
RHD
InterHand2.6M
COCO-WholeBody
ICVL
NYU Hand
MSRA Hand
First-Person Hand Action Benchmark
EgoDexter
Latest papers
HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud
Extracting keypoint locations from input hand frames, known as 3D hand pose estimation, is a critical task in various human-computer interaction applications.
Single-to-Dual-View Adaptation for Egocentric 3D Hand Pose Estimation
These two stereo constraints are used in a complementary manner to generate pseudo-labels, allowing reliable adaptation.
Fingerspelling PoseNet: Enhancing Fingerspelling Translation with Pose-Based Transformer Models
pooyafayyaz/fingerspelling-posenet
•
•
We also propose a novel two-stage inference approach that re-ranks the hypotheses using the language model capabilities of the decoder.
RenderIH: A Large-scale Synthetic Dataset for 3D Interacting Hand Pose Estimation
adwardlee/renderih
•
•
ICCV 2023
The current interacting hand (IH) datasets are relatively simplistic in terms of background and texture, with hand joints being annotated by a machine annotator, which may result in inaccuracies, and the diversity of pose distribution is limited.
OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision
deepwise888/ochid-fi
•
•
ICCV 2023
To overcome the challenge in labeling RF imaging given its human incomprehensible nature, OCHID-Fi employs a cross-modality and cross-domain training process.
MuTr: Multi-Stage Transformer for Hand Pose Estimation from Full-Scene Depth Image
This work presents a novel transformer-based method for hand pose estimation—DePOTR.
A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Image
changlongjianggit/a2j-transformer
•
•
CVPR 2023
3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimation method-to RGB domain under interacting hand condition.
Robustness Evaluation in Hand Pose Estimation Models using Metamorphic Testing
We found that on average more than 80\% of the hands could not be identified by BodyHands, and at least 50\% of hands could not be identified by MediaPipe hands when diagonal motion blur is introduced, while an average of more than 50\% of strongly underexposed hands could not be correctly estimated by NSRM hand.
HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning
Recent advancements in 3D hand pose estimation have shown promising results, but its effectiveness has primarily relied on the availability of large-scale annotated datasets, the creation of which is a laborious and costly process.
Handy: Towards a High Fidelity 3D Hand Shape and Appearance Model
rolpotamias/handy
•
•
CVPR 2023
Currently, most of the state-of-the-art reconstruction and pose estimation methods rely on the low polygon MANO model.
