This is a summary of research on noisy correspondence. There may be omissions. If anything is missing please get in touch with us. Our emails: linyijie.gm@gmail.com yangmouxing@gmail.com qinyang.gm@gmail.com
Multi-granularity Correspondence Learning from Long-term Noisy Videos [ICLR 2024, Oral]
This repo contains the code and data of "Graph Matching with Bi-level Noisy Correspondence".
Noise of Web (NoW) is a challenging noisy correspondence learning (NCL) benchmark containing 100K image-text pairs for robust image-text matching/retrieval models.
[CVPR 2025] Official Pytorch implementation of "Learning with Noisy Triplet Correspondence for Composed Image Retrieval".
[CVPR 2026] Pytorch Code for the paper "Bootstrapping Multi-view Learning for Test-time Noisy Correspondence"
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