Research map / Vision-language and multimodal / Cross-modal learning
Interact, Embed, and EnlargE: Boosting Modality-Specific Representations for Multi-Modal Person Re-identification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add cross-modal interaction (CIM) (ablation) | Three-stream Re-ID network · RGBNT201 | mAP: 21.55 -> 31.94 | Helped |
| add multi-modal margin loss (3M) (ablation) | CIM network · RGBNT201 | mAP: 31.94 -> 39.24 | Helped |
| add relation-based embedding (REM) (ablation) | CIM + 3M network · RGBNT201 | mAP: 39.24 -> 46.42 | Helped |
| add cross-modal interaction, global-to-local embedding, and 3M loss | IEEE with ResNet50 · RGBNT201 | mAP: 38.46 -> 46.42 | Helped |
| add cross-modal interaction, global-to-local embedding, and 3M loss | IEEE with ResNet50 · Market1501 (multi-modal version) | mAP: 60.93 -> 64.32 | Helped |
Closest papers by meaning
- FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification (ICML 2025 · similarity 0.89)
- Heterogeneous Test-Time Training for Multi-Modal Person Re-identification (AAAI 2024 · similarity 0.89)
- ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model (NeurIPS 2025 · similarity 0.89)
- MDReID: Modality-Decoupled Learning for Any-to-Any Multi-Modal Object Re-Identification (NeurIPS 2025 · similarity 0.89)
- Multi-Modal Object Re-identification via Sparse Mixture-of-Experts (ICML 2025 · similarity 0.88)
- Implicit Discriminative Knowledge Learning for Visible-Infrared Person Re-Identification (CVPR 2024 · similarity 0.87)
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