Image Retrieval On Fashion Iq
Métriques
(Recall@10+Recall@50)/2
Recall@10
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | (Recall@10+Recall@50)/2 | Recall@10 |
|---|---|---|
| candidate-set-re-ranking-for-composed-image | 62.15 | 51.17 |
| improving-composed-image-retrieval-via | 66.41 | 56.37 |
| composed-image-retrieval-using-contrastive | 55.36 | - |
| improving-composed-image-retrieval-via | 66.41 | - |
| cosmo-content-style-modulation-for-image | 39.45 | - |
| compositional-learning-of-image-text-query | 20.6 | - |
| data-roaming-and-early-fusion-for-composed | 59.73 | 48.79 |
| curlingnet-compositional-learning-between | 38.45 | - |
| ranking-aware-uncertainty-for-text-guided | 61.32 | - |
| relieving-triplet-ambiguity-consensus-network | 51.34 | - |
| bi-directional-training-for-composed-image | 55.4 | - |
| effective-conditioned-and-composed-image | 47.21 | - |
| rtic-residual-learning-for-text-and-image | 40.64 | - |
| megapairs-massive-data-synthesis-for | 46.1 | 35.6 |
| composed-image-retrieval-with-text-feedback | 50.61 | - |
| conditioned-and-composed-image-retrieval | 50.03 | - |
| image-search-with-text-feedback-by | 35.38 | - |
| sentence-level-prompts-benefit-composed-image | 64.85 | 54.92 |
| ranking-aware-uncertainty-for-text-guided | 55.27 | - |
| composed-image-retrieval-with-text-feedback | 47.28 | - |
| cala-complementary-association-learning-for | 57.96 | 46.69 |