Image Retrieval On Flickr30K
Metrics
Recall@1
Recall@10
Recall@5
Results
Performance results of various models on this benchmark
| Paper Title | Code | ||||
|---|---|---|---|---|---|
| BLIP-2 ViT-L (zero-shot, 1K test set) | 88.6 | 98.9 | 97.6 | BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models | |
| BLIP-2 ViT-G (zero-shot, 1K test set) | 89.7 | 98.9 | 98.1 | BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models | |
| HADA | 81.36 | 98.02 | 95.94 | HADA: A Graph-based Amalgamation Framework in Image-text Retrieval | |
| MaMMUT (ours) | 82.5 | 98 | 96 | MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks | |
| ALBEF | 79.76 | 97.72 | 95.3 | HADA: A Graph-based Amalgamation Framework in Image-text Retrieval | |
| UNITER | 75.56 | 96.76 | 94.08 | HADA: A Graph-based Amalgamation Framework in Image-text Retrieval | |
| LGSGM | 57.4 | 90.2 | 84.1 | A Deep Local and Global Scene-Graph Matching for Image-Text Retrieval | |
| GSMN | - | 89 | 82.3 | A Deep Local and Global Scene-Graph Matching for Image-Text Retrieval | |
| VisualSparta | 57.4 | 88.1 | 82.0 | VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words |
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