CVPR 2023 - CrOC: Cross-View Online Clustering for Dense Visual Representation Learning

In this episode we discuss CrOC: Cross-View Online Clustering for Dense Visual Representation Learning by Thomas Stegmüller, Tim Lebailly, Behzad Bozorgtabar, Tinne Tuytelaars, Jean-Philippe Thiran. The paper proposes a method called Cross-view consistency objective with an Online Clustering (CrOC) to learn dense visual representations without labels in scene-centric data. The method uses an online clustering algorithm that operates on both views' features, avoiding issues with content not represented in both views and ambiguous object matching. The proposed method shows excellent performance in linear and unsupervised segmentation transfer tasks on various datasets and video object segmentation. Pre-trained models and code are publicly available.