Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add semantic distillation to the visual→attribute subnet (ablation) | MSDN · CUB and SUN | H: 55.4 -> 60.8; 33.8 -> 38.6 | Helped |
| Add semantic distillation to the attribute→visual subnet (ablation) | MSDN · CUB and SUN | H: 65.4 -> 67.5; 38.5 -> 38.7 | Helped |
| Use the attribute→visual subnet alone instead of the visual→attribute subnet (ablation) | MSDN without distillation · CUB and SUN | H: 55.4 -> 65.4; 33.8 -> 38.5 | Helped |
| Combine both attention subnets and distill with both JSD and ℓ2 (ablation) | MSDN · CUB and SUN | H: 67.5 -> 68.1; 40.8 -> 41.3 | Helped |
| Use JSD alone in place of the combined JSD and ℓ2 distillation loss (ablation) | MSDN · CUB and SUN | H: 68.1 -> 67.0; 41.3 -> 39.4 | Hurt |
| Use ℓ2 alone in place of the combined JSD and ℓ2 distillation loss (ablation) | MSDN · CUB and SUN | H: 68.1 -> 67.6; 41.3 -> 40.8 | Hurt |
| Use both attention subnets and their mutual semantic distillation rather than the global-feature baseline (ablation) | MSDN · CUB and SUN | H: 49.1 -> 68.1; 30.5 -> 41.3 | Helped |
Closest papers by meaning
- Progressive Semantic-Guided Vision Transformer for Zero-Shot Learning (CVPR 2024 · similarity 0.91)
- ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning (ICLR 2025 · similarity 0.90)
- ZeroMamba: Exploring Visual State Space Model for Zero-Shot Learning (AAAI 2025 · similarity 0.90)
- Epsilon: Exploring Comprehensive Visual-Semantic Projection for Multi-Label Zero-Shot Learning (AAAI 2025 · similarity 0.90)
- Attend and Enrich: Enhanced Visual Prompt for Zero-Shot Learning (AAAI 2025 · similarity 0.90)
- Class Semantic Attribute Perception Guided Zero-Shot Learning (AAAI 2025 · similarity 0.90)
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