Research map / Detection and segmentation / Open-set and few-shot detection
Visual Boundary Knowledge Translation for Foreground Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add boundary-aware self-supervision (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 92.12 -> 92.74 | Helped |
| Add pseudo triplets to the boundary discriminators (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 92.39 -> 92.74 | Helped |
| Add the inner boundary discriminator (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 87.06 -> 92.74 | Helped |
| Add the outer boundary discriminator (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 90.98 -> 92.74 | Helped |
| Use separate inner and outer discriminators instead of one combined discriminator (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 82.85 -> 92.74 | Helped |
| Provide 10 instead of zero labeled target samples (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 48.90 -> 92.74 | Helped |
| Increase labeled target samples from 10 to 20 (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 92.74 -> 92.87 | Helped |
| Increase labeled target samples from 20 to 50 (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 92.87 -> 94.00 | Helped |
| Increase labeled target samples from 50 to 100 (ablation) | Trans-Net · HumanMatting (Humans ← MixAll−) | MIoU: 94.00 -> 94.09 | Helped |
| Translate boundary knowledge from a mixed-category source dataset rather than Birds | Trans-Net · Humans | MIoU: 88.86 -> 90.46 | Helped |
Closest papers by meaning
- FOCUS: Towards Universal Foreground Segmentation (AAAI 2025 · similarity 0.89)
- Devil Is in the Edges: Learning Semantic Boundaries From Noisy Annotations (CVPR 2019 · similarity 0.89)
- Semantic Segmentation With Boundary Neural Fields (CVPR 2016 · similarity 0.88)
- Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation (CVPR 2016 · similarity 0.88)
- Learning Hierarchical Image Segmentation For Recognition and By Recognition (ICLR 2024 · similarity 0.87)
- Subobject-level Image Tokenization (ICML 2025 · similarity 0.86)
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