Papers › CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
Geonmo Gu, Sanghyuk Chun, Wonjae Kim, HeeJae Jun, Yoohoon Kang, Sangdoo Yun
This paper proposes a novel diffusion-based model, CompoDiff, for solving zero-shot Composed Image Retrieval (ZS-CIR) with latent diffusion. This paper also introduces a new synthetic dataset, named SynthTriplets18M, with 18.8 million reference images, conditions, and corresponding target image triplets to train CIR models. CompoDiff and SynthTriplets18M tackle the shortages of the previous CIR approaches, such as poor generalizability due to the small dataset scale and the limited types of conditions. CompoDiff not only achieves a new state-of-the-art on four ZS-CIR benchmarks, including FashionIQ, CIRR, CIRCO, and GeneCIS, but also enables a more versatile and controllable CIR by accepting various conditions, such as negative text, and image mask conditions. CompoDiff also shows the controllability of the condition strength between text and image queries and the trade-off between inference speed and performance, which are unavailable with existing CIR methods. The code and dataset are available at https://github.com/navervision/CompoDiff
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRCO | CompoDiff (CLIP G/14) | mAP@10 | 17.71 | #29 of 43 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRCO | CompoDiff (CLIP L/14) | mAP@10 | 13.51 | #34 of 43 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRR | CompoDiff (CLIP G/14) | R@5 | 57.61 | #30 of 47 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | CIRR | CompoDiff (CLIP L/14) | R@5 | 54.36 | #40 of 47 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | Fashion IQ | CompoDiff (CLIP G/14) | (Recall@10+Recall@50)/2 | 45.37 | #11 of 41 | Archive leaderboard | report |
| Zero-Shot Composed Image Retrieval (ZS-CIR) | Fashion IQ | CompoDiff (CLIP L/14) | (Recall@10+Recall@50)/2 | 44.11 | #16 of 41 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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