BUAADreamer/SPN4CIR
[ACM MM 2024] Improving Composed Image Retrieval via Contrastive Learning with Scaling Positives and Negatives
This project helps e-commerce and marketing professionals find specific images in a large catalog by combining an existing image with text descriptions. You input a reference image and a phrase describing how it should be modified (e.g., "make it red"), and the system outputs relevant target images. It's designed for anyone needing to efficiently search visual content using both visual and textual cues.
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Use this if you need to quickly locate images that are visually similar to a given example but with specific textual modifications, like finding a different color of a dress shown in a picture.
Not ideal if your image retrieval needs are solely based on keywords or exact image matching without any textual modification to an existing image.
Stars
39
Forks
4
Language
Python
License
MIT
Category
Last pushed
Sep 09, 2025
Commits (30d)
0
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