Research map / Vision-language and multimodal / Cross-modal learning
Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| PRDH (intra+inter-modal pairwise losses, decorrelation) vs DCMH | deep cross-modal hashing · MIRFlickr Image->Text | MAP: 0.7035 -> 0.7128 (32 bits) | Helped |
| PRDH (intra+inter-modal pairwise losses, decorrelation) vs DCMH | deep cross-modal hashing · MIRFlickr Text->Image | MAP: 0.7487 -> 0.7540 (32 bits) | Helped |
| PRDH (intra+inter-modal pairwise losses, decorrelation) vs DCMH | deep cross-modal hashing · NUS-WIDE Image->Text | MAP: 0.6167 -> 0.6529 (32 bits) | Helped |
| PRDH (intra+inter-modal pairwise losses, decorrelation) vs DCMH | deep cross-modal hashing · NUS-WIDE Text->Image | MAP: 0.6487 -> 0.6961 (32 bits) | Helped |
Closest papers by meaning
- Deep Cross-Modal Hashing (CVPR 2017 · similarity 0.92)
- Ranking-Based Deep Cross-Modal Hashing (AAAI 2019 · similarity 0.92)
- Dual Deep Neural Networks Cross-Modal Hashing (AAAI 2018 · similarity 0.91)
- Lightweight Contrastive Distilled Hashing for Online Cross-modal Retrieval (AAAI 2025 · similarity 0.91)
- Dual Self-Paced Cross-Modal Hashing (AAAI 2024 · similarity 0.90)
- An End-To-End Graph Attention Network Hashing for Cross-Modal Retrieval (NeurIPS 2024 · similarity 0.89)
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