Research map / Label-efficient and robust learning / Recognition and long-tail
Deep MIML Network
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add 3D sub-concept layer with two-stage pooling on conv features | VGG-16 · MS-COCO | mAP: 57 % -> 60.5% | Helped |
| add 3D sub-concept layer | VGG-16 · MS-COCO | F1: 0.650 -> 0.637 | Hurt |
| sentence bag with sub-concept layer instead of whole-review MLP | skip-thought features · Yelp | mAP: 0.325 -> 0.330 | Helped |
| DeepMIML instead of KISAR | hand-crafted MIML instances · MIML Scene | Hamming loss: 0.032 -> 0.026 | Helped |
| vary number of sub-concepts K (ablation) | DeepMIML · Yelp | mAP | No clear effect |
Closest papers by meaning
- T-MDML: Triplet-based Multiple Distance Metric Learning for Multi-Instance Multi-Label Classification with Label Correlation (AAAI 2025 · similarity 0.85)
- Multi-Instance Multi-Label Classification from Crowdsourced Labels (AAAI 2025 · similarity 0.83)
- Fast Multi-Instance Partial-Label Learning (AAAI 2025 · similarity 0.82)
- Are Multiple Instance Learning Algorithms Learnable for Instances? (NeurIPS 2024 · similarity 0.82)
- Multi-View Multi-Label Classification via View-Label Matching Selection (AAAI 2025 · similarity 0.81)
- Self-Paced Unified Representation Learning for Hierarchical Multi-Label Classification (AAAI 2024 · similarity 0.81)
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