Summary of Hi5: 2d Hand Pose Estimation with Zero Human Annotation, by Masum Hasan et al.
Hi5: 2D Hand Pose Estimation with Zero Human Annotation
by Masum Hasan, Cengiz Ozel, Nina Long, Alexander Martin, Samuel Potter, Tariq Adnan, Sangwu Lee, Amir Zadeh, Ehsan Hoque
First submitted to arxiv on: 5 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Graphics (cs.GR); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Hi5 dataset is a large-scale synthetic collection of high-quality images depicting diverse hand poses, genders, and skin colors. The method for generating this dataset requires no human annotation or validation, leveraging advancements in computer graphics to create 3D hand models with dynamic environments and camera movements. This allows precise control over data diversity and representation, enabling robust and fair model training. The generated dataset contains 583,000 images with accurate pose annotations, which can be used to train pose estimation models that perform competitively on real-hand benchmarks. Furthermore, these models surpass those trained with real data when tested on occlusions and perturbations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way of creating hand pose pictures is being proposed. This method doesn’t need any human help or verification, which makes it faster and cheaper than traditional ways of collecting data. The computer-generated images show different types of hands, skin colors, and genders, and can be used to train machines that recognize hand poses. The new dataset has 583,000 pictures with correct pose information, which helps machines learn better. When tested on real-world scenarios, the trained models do well even when there are obstacles or changes. |
Keywords
» Artificial intelligence » Pose estimation
