LRVS-Fashion: Extending Visual Search with Referring Instructions

Understand

This paper introduces a new challenge for image similarity search in the context of fashion, addressing the inherent ambiguity in this domain stemming from complex images.

• We present Referred Visual Search (RVS), a task allowing users to define more precisely the desired similarity, following recent interest in the industry.
• We release a new large public dataset, LRVS-Fashion, consisting of 272k fashion products with 842k images extracted from fashion catalogs, designed explicitly for this task.
• However, unlike traditional visual search methods in the industry, we demonstrate that superior performance can be achieved by bypassing explicit object detection and adopting weakly-supervised conditional contrastive learning on image tuples.