Research map / 3D vision / Human pose estimation
BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Train the Holi CNN on BigHand2.2M rather than ICVL | Holi CNN · NYU test | mean error (mm): 35.1 -> 20.6 | Helped |
| Train the Holi CNN on BigHand2.2M rather than NYU | Holi CNN · ICVL test | mean error (mm): 20.1 -> 14.9 | Helped |
| Train the Holi CNN on BigHand2.2M rather than MSRC | Holi CNN · ICVL test | mean error (mm): 25.3 -> 14.9 | Helped |
| Train the Holi CNN on BigHand2.2M rather than MSRC | Holi CNN · NYU test | mean error (mm): 30.8 -> 20.6 | Helped |
| Train the Holi CNN on BigHand2.2M rather than MSRC | Holi CNN · MSRC test | mean error (mm): 21.3 -> 43.7 | Hurt |
| Increase the fraction of BigHand2.2M training data (ablation) | Holi CNN · ICVL, NYU, MSRC, and BigHand2.2M tests | estimation performance | Helped |
| Train on BigHand2.2M instead of the corresponding benchmark training data | Holi CNN · ICVL test | mean error (mm): 12.3 -> 14.9 | Hurt |
| Train on BigHand2.2M rather than NYU | Holi CNN · NYU test | mean error (mm): 21.4 -> 20.6 | Helped |
Closest papers by meaning
- DeepHand: Robust Hand Pose Estimation by Completing a Matrix Imputed With Deep Features (CVPR 2016 · similarity 0.91)
- Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals (CVPR 2018 · similarity 0.91)
- Efficiently Creating 3D Training Data for Fine Hand Pose Estimation (CVPR 2016 · similarity 0.91)
- SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training (ICLR 2025 · similarity 0.88)
- Analyzing the Synthetic-to-Real Domain Gap in 3D Hand Pose Estimation (CVPR 2025 · similarity 0.88)
- GigaHands: A Massive Annotated Dataset of Bimanual Hand Activities (CVPR 2025 · similarity 0.88)
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