Research map / Detection and segmentation / Weakly supervised detection and segmentation
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use separate image-based encoder training and video-based segmentation training rather than learning the whole model directly from videos | Weakly supervised semantic segmentation · PASCAL VOC 2012 val | mIoU | Helped |
| Replace the [cite] video set with automatically collected YouTube videos (ablation) | Ours · PASCAL VOC 2012 val | mIoU: 49.2 -> 55.2 | Helped |
| Add domain adaptation by generating image segmentation labels and fine-tuning on still images (ablation) | Ours with YouTube videos · PASCAL VOC 2012 val | mIoU: 55.2 -> 58.1 | Helped |
| Use web-video-generated segmentation supervision with image-level labels | Weakly supervised semantic segmentation · PASCAL VOC 2012 val | mIoU: 50.7 -> 58.1 | Helped |
Closest papers by meaning
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- Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic Segmentation (CVPR 2024 · similarity 0.88)
- W2P: Switching from Weak Supervision to Partial Supervision for Semantic Segmentation (AAAI 2024 · similarity 0.88)
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