Zihua Zhao

Mitigating Noisy Correspondence by Geometrical Structure Consistency Learning

2024 · arXiv (Cornell University)

Noisy correspondence that refers to mismatches in cross-modal data pairs, is prevalent on human-annotated or web-crawled datasets. Prior approaches to leverage such data mainly consider the application of uni-modal noisy label learning without amending the …