Research map / 3D vision / Human pose estimation
GANerated Hands for Real-Time 3D Hand Tracking From Monocular RGB
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace synthetic-only training images with GANerated images (ablation) | RegNet · Stereo dataset (12 sequences) | 3D PCK@50mm: ≈0.55 -> ≈0.80 | Helped |
| add color augmentation to synthetic training images (ablation) | RegNet · Stereo dataset (12 sequences) | 3D PCK@50mm | Helped |
| add the ProjLayer to link and refine 2D and 3D predictions (ablation) | RegNet trained with GANerated images · Stereo dataset | 3D PCK | Helped |
| use GANerated images instead of synthetic-only training data (ablation) | RegNet · Stereo dataset | 3D PCK | Helped |
| use the proposed method rather than Zimmermann and Brox | monocular RGB hand pose estimation · Dexter+Object | 2D PCK | Helped |
| use the proposed method rather than Zimmermann and Brox | monocular RGB hand pose estimation · EgoDexter | 2D PCK | Helped |
| use the proposed method rather than existing methods | monocular RGB hand pose estimation · Stereo dataset | 3D PCK | Helped |
| use RGB-only input rather than RGB-D input | the proposed hand tracker · Dexter+Object | mean error: ≈5cm vs. ≈2cm | Hurt |
Closest papers by meaning
- 3D Hand Shape and Pose Estimation From a Single RGB Image (CVPR 2019 · similarity 0.91)
- 3D Convolutional Neural Networks for Efficient and Robust Hand Pose Estimation From Single Depth Images (CVPR 2017 · similarity 0.89)
- Pushing the Envelope for RGB-Based Dense 3D Hand Pose Estimation via Neural Rendering (CVPR 2019 · similarity 0.89)
- ComPose: When to Trust Hands for Object Pose Tracking (NeurIPS 2026 · similarity 0.88)
- FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generation (CVPR 2025 · similarity 0.88)
- Reconstructing Hands in 3D with Transformers (CVPR 2024 · similarity 0.87)
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