Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval

arXiv cs.CV1mo4 min read

arXiv:2607.00374v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification. While supervised CIR relies on costly triplets, Zero-Shot CIR (ZS-CIR) alleviates this reliance through proxy tasks trained on image-text pairs. However, existing proxy tasks primarily enhance visual and textual representations to accommodate a predefined composition mechanism such as pseudo-word injection into a frozen text encoder or linear feature arithmetic. As a result, the composition function itself remains unlearned, limiting the mod

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Learning to Compose: Revisiting Proxy Task Design for Zero-Shot Composed Image Retrieval

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