Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

arXiv:2306.05272v5 Announce Type: replace-cross
Abstract: The advent of large pre-trained models has brought about a paradigm shift in both visual representation learning and natural language processing. However, clustering unlabeled images, as a fundamental and classic machine learning problem, still lacks an effective solution, particularly for large-scale datasets. In this paper, we propose a novel image clustering pipeline that leverages the powerful feature representation of large pre-trained models such as CLIP and cluster images effectively and efficiently at scale. We first …

age arxiv clustering cs.cv cs.lg image pretrained models rate type via