MELT: Improve Composed Image Retrieval via the Modification Frequentation-Rarity Balance Network
Composed Image Retrieval (CIR) uses a reference image and a modification text as a query to retrieve a target image satisfying the requirement of ``modifying the reference image according to the text instructions''. However, existing CIR methods face two limitations: (1) frequency bias leading to ``Rare Sample Neglect'', and (2) susceptibility of similarity scores to interference from hard negative samples and noise. To address these limitations, we confront two key challenges: asymmetric rare semantic localization and robust similarity estimation under hard negative samples. To solve these challenges, we propose the Modification frEquentation-rarity baLance neTwork MELT. MELT assigns inc...
| Authors | Guozhi Qiu, Zhiwei Chen, Zixu Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 31 March 2026 |
| Last updated at source | 31 March 2026 |
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