Uncover Underlying Correspondence for Robust Multi-view Clustering

TL;DR

Multi-view clustering (MVC) aims to group unlabeled data into semantically meaningful clusters by leveraging cross-view consistency. However, real-world datasets collected from the web often suffer from noisy correspondence (NC), which breaks the consistency prior and results in unreliable alignments.

Opening excerpt from the authors’ abstract. source