Research map / Label-efficient and robust learning / Domain adaptation and generalization
Universal Source-Free Domain Adaptation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use USFDA instead of UAN | Office-Home universal adaptation · Office-Home (12 transfers; Avg) | T_avg: 77.02 -> 77.03 | Helped |
| Use USFDA instead of UAN | Office-31 universal adaptation · Office-31 (6 transfers; Avg) | T_avg: 89.24 -> 90.18 | Helped |
| Use USFDA instead of UAN | VisDA S→R adaptation · VisDA S→R | T_avg: 60.83 -> 63.92 | Helped |
| Use USFDA instead of UAN | ImageNet-Caltech adaptation · ImageNet-Caltech I→C | T_avg: 75.28 -> 76.85 | Helped |
| Use USFDA instead of UAN | ImageNet-Caltech adaptation · ImageNet-Caltech C→I | T_avg: 70.17 -> 72.13 | Helped |
| Use USFDA instead of UAN* | Office-31 universal adaptation · Office-31 (6 transfers; Avg) | T_unk: 42.54 -> 79.32 | Helped |
| Use the generative classifier with simulated labeled negative samples | USFDA · Office-31 A→D; no shared categories | one-shot recognition accuracy: 13.43% -> 64.72% | Helped |
| Reduce the number of simulated negative classes (ablation) | USFDA procurement stage · Office-31 A→D | T_avg | Hurt |
| Form negative classes by combining three or more images instead of image pairs (ablation) | USFDA procurement stage · Office-31 A→D | positive-source classification accuracy | Hurt |
| Vary β over the tested range (ablation) | USFDA deployment stage · Office-31 A→D | adaptation accuracy | No clear effect |
Closest papers by meaning
- Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety (CVPR 2025 · similarity 0.91)
- Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation (AAAI 2025 · similarity 0.91)
- Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective (CVPR 2024 · similarity 0.90)
- Distinguish Then Exploit: Source-free Open Set Domain Adaptation via Weight Barcode Estimation and Sparse Label Assignment (CVPR 2025 · similarity 0.89)
- Dynamic Target Distribution Estimation for Source-Free Open-Set Domain Adaptation (AAAI 2025 · similarity 0.89)
- Can We Evaluate Domain Adaptation Models Without Target-Domain Labels? (ICLR 2024 · similarity 0.89)
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