Image Retrieval
Image Retrieval is a fundamental and long-standing computer vision task that involves finding images similar to a given query from a large database. It is often considered a form of fine-grained, instance-level classification. The task is integral to image recognition alongside classification and cross-modal retrieval. By leveraging visual similarity and other criteria, image retrieval enables users to efficiently discover relevant images, making it a crucial tool in applications such as search and recommendation.
Extending CLIP for Category-to-image Retrieval in E-commerce
( Image credit: DELF )
Papers
Showing 1–10 of 2239 papers
All datasetsROxford (Hard)ROxford (Medium)RParis (Hard)RParis (Medium)CREPE (Compositional REPresentation Evaluation)Fashion IQFlickr30K 1K testCIRRSOPFlickr30k-CNOxf5kFlickr30k
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | TMCIR | (Recall@5+Recall_subset@1)/2 | 83.46 | — | Unverified |
| 2 | SPN4CIR (SPRC) | (Recall@5+Recall_subset@1)/2 | 82.69 | — | Unverified |
| 3 | SPRC2 | (Recall@5+Recall_subset@1)/2 | 82.66 | — | Unverified |
| 4 | SPRC | (Recall@5+Recall_subset@1)/2 | 81.39 | — | Unverified |
| 5 | Candidate Set Re-ranking | (Recall@5+Recall_subset@1)/2 | 80.9 | — | Unverified |
| 6 | CaLa | (Recall@5+Recall_subset@1)/2 | 78.74 | — | Unverified |
| 7 | CASE (Pre-trained on LaSCo.Ca) | (Recall@5+Recall_subset@1)/2 | 78.25 | — | Unverified |
| 8 | CASE | (Recall@5+Recall_subset@1)/2 | 77.5 | — | Unverified |
| 9 | VISTA (base) | (Recall@5+Recall_subset@1)/2 | 75.9 | — | Unverified |
| 10 | MMRet-MLLM | (Recall@5+Recall_subset@1)/2 | 75.7 | — | Unverified |