CIRCO (Composed Image Retrieval on Common Objects in context)
Introduced by Baldrati et al. in Zero-Shot Composed Image Retrieval with Textual Inversion
CIRCO (Composed Image Retrieval on Common Objects in context) is an open-domain benchmarking dataset for Composed Image Retrieval (CIR) based on real-world images from COCO 2017 unlabeled set. It is the first CIR dataset with multiple ground truths and aims to address the problem of false negatives in existing datasets. CIRCO comprises a total of 1020 queries, randomly divided into 220 and 800 for the validation and test set, respectively, with an average of 4.53 ground truths per query.
Source: Zero-Shot Composed Image Retrieval with Textual InversionBenchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
CIRCO
|
CIReVL
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
