Research map / Label-efficient and robust learning / Recognition and long-tail
Latent Semantic Aware Multi-View Multi-Label Classification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use latent-semantic multi-view matrix factorization | multi-view multi-label · Corel5k | average precision: .425±˙004 -> .462±.003 (vs LrMMC-2) | Helped |
| use latent-semantic multi-view matrix factorization | multi-view multi-label · ESP Game | average precision: .272±.002 -> .345±.001 (vs MLkNN) | Helped |
| use latent-semantic multi-view matrix factorization | multi-view multi-label · PASCAL VOC | ranking loss: .163±˙002 -> .149±.001 (vs LrMMC-2) | Helped |
| use latent-semantic multi-view matrix factorization | multi-view multi-label · ESP Game | ranking loss: .153±.001 -> .161±.001 (vs LrMMC-2) | Hurt |
| use multiple views instead of best single view (ablation) | Ours · Corel5k | average precision: .419±.014 -> .462±.003 | Helped |
| use multiple views instead of best single view (ablation) | Ours · PASCAL VOC | average precision: .528±.006 -> .610±.001 | Helped |
| concatenate views instead of best single view | single-view multi-label methods · benchmarks | average precision | Helped |
Closest papers by meaning
- Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling (ICML 2024 · similarity 0.91)
- Incomplete Multi-View Multi-label Learning via Disentangled Representation and Label Semantic Embedding (CVPR 2025 · similarity 0.90)
- Multi-View Multi-Label Classification via View-Label Matching Selection (AAAI 2025 · similarity 0.88)
- View-Category Interactive Sharing Transformer for Incomplete Multi-View Multi-Label Learning (CVPR 2024 · similarity 0.88)
- Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification (ICML 2025 · similarity 0.88)
- CFDM: Contrastive Fusion and Disambiguation for Multi-View Partial-Label Learning (AAAI 2025 · similarity 0.88)
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