Research map / Architectures and efficiency / CNN design
Gesture Recognition: Focus on the Hands
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add hand-focused spatial channels and sparse fusion | FOANet · ChaLearn IsoGD test | accuracy: 67.71 -> 82.07 | Helped |
| add hand-focused spatial channels and sparse fusion | FOANet · NVIDIA test | accuracy: 83.8 -> 91.28 | Helped |
| replace average fusion with sparse fusion across 12 channels (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 70.37 -> 82.07 | Helped |
| replace average fusion with sparse fusion (ablation) | FOANet · NVIDIA test | accuracy: 85.26 -> 91.28 | Helped |
| use 7 channels instead of all 12 with sparse fusion (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 82.07 -> 78.90 | Hurt |
| select 7 channels and use average fusion instead of averaging all 12 (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 70.37 -> 71.93 | Helped |
| replace sparse fusion with concatenation of channel features (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 82.07 -> 59.44 | Hurt |
| use focus channels without global channels (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 67.5 -> 77.61 | Helped |
| use all channels rather than global channels only (ablation) | FOANet · ChaLearn IsoGD test | accuracy: 67.5 -> 82.07 | Helped |
Closest papers by meaning
- Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network (CVPR 2016 · similarity 0.87)
- Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition (AAAI 2021 · similarity 0.86)
- LD-ConGR: A Large RGB-D Video Dataset for Long-Distance Continuous Gesture Recognition (CVPR 2022 · similarity 0.84)
- SocialGesture: Delving into Multi-person Gesture Understanding (CVPR 2025 · similarity 0.83)
- Hand1000: Generating Realistic Hands from Text with Only 1,000 Images (AAAI 2025 · similarity 0.82)
- A Wireframe-Based Approach for Classifying and Acquiring Proficiency in the American Sign Language (Student Abstract) (AAAI 2024 · similarity 0.81)
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