Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912503801315328 |
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| author | Maity, Subhajit Bhunia, Ayan Kumar Koley, Subhadeep Chowdhury, Pinaki Nath Sain, Aneeshan Song, Yi-Zhe |
| author_facet | Maity, Subhajit Bhunia, Ayan Kumar Koley, Subhadeep Chowdhury, Pinaki Nath Sain, Aneeshan Song, Yi-Zhe |
| contents | Keypoint detection, integral to modern machine perception, faces challenges in few-shot learning, particularly when source data from the same distribution as the query is unavailable. This gap is addressed by leveraging sketches, a popular form of human expression, providing a source-free alternative. However, challenges arise in mastering cross-modal embeddings and handling user-specific sketch styles. Our proposed framework overcomes these hurdles with a prototypical setup, combined with a grid-based locator and prototypical domain adaptation. We also demonstrate success in few-shot convergence across novel keypoints and classes through extensive experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07994 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection Maity, Subhajit Bhunia, Ayan Kumar Koley, Subhadeep Chowdhury, Pinaki Nath Sain, Aneeshan Song, Yi-Zhe Computer Vision and Pattern Recognition I.4.0; I.4.9 Keypoint detection, integral to modern machine perception, faces challenges in few-shot learning, particularly when source data from the same distribution as the query is unavailable. This gap is addressed by leveraging sketches, a popular form of human expression, providing a source-free alternative. However, challenges arise in mastering cross-modal embeddings and handling user-specific sketch styles. Our proposed framework overcomes these hurdles with a prototypical setup, combined with a grid-based locator and prototypical domain adaptation. We also demonstrate success in few-shot convergence across novel keypoints and classes through extensive experiments. |
| title | Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection |
| topic | Computer Vision and Pattern Recognition I.4.0; I.4.9 |
| url | https://arxiv.org/abs/2507.07994 |