Research map / Detection and segmentation / Open-set and few-shot detection
A Causal Debiasing Framework for Unsupervised Salient Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Apply causal debiasing with DSR pseudo-labels | Strong baseline USOD model · DUTS-TE | Eξ: .843 -> .855 | Helped |
| Apply causal debiasing with DSR pseudo-labels | Strong baseline USOD model · DUTS-TE | Fβ: .747 -> .764 | Helped |
| Apply causal debiasing with DSR pseudo-labels | Strong baseline USOD model · DUTS-TE | M: .070 -> .064 | Helped |
| Add explicit low- and high-level visual contrast fusion (ablation) | Vanilla USOD baseline · DUTS-TE | Eξ: .787 -> .843 | Helped |
| Add causal de-confounding to the contrast fusion block (ablation) | Contrast Fusion Block model · DUTS-TE | Eξ: .843 -> .844 | Helped |
| Add image-level weighting based on spatial distribution bias (ablation) | De-confounded USOD model · DUTS-TE | Eξ: .844 -> .855 | Helped |
| Use res3 rather than res2 as the low-level contrast feature (ablation) | DUTS DCFD with ResNet-50 · DUTS-TE | Eξ: .855 -> .856 | No clear effect |
| Use res5 rather than res4 as the high-level contrast feature (ablation) | DUTS DCFD with ResNet-50 · DUTS-TE | Eξ: .840 -> .855 | Helped |
| Train on DUTS rather than MSRA-B (ablation) | Causal debiasing framework · DUTS-TE | Eξ | Mixed |
| Use DCFD instead of EDNS | Unsupervised salient object detection · DUTS-TE | Eξ: .847 -> .855 | Helped |
Closest papers by meaning
- Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection (ICML 2024 · similarity 0.88)
- Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection (CVPR 2024 · similarity 0.87)
- DiMSOD: A Diffusion-Based Framework for Multi-Modal Salient Object Detection (AAAI 2025 · similarity 0.86)
- Long-tailed Object Detection Pretraining: Dynamic Rebalancing Contrastive Learning with Dual Reconstruction (NeurIPS 2024 · similarity 0.86)
- UN-DETR: Promoting Objectness Learning via Joint Supervision for Unknown Object Detection (AAAI 2025 · similarity 0.86)
- Unsupervised Salient Instance Detection (CVPR 2024 · similarity 0.86)
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