UniVIP: A Unified Framework for Self-Supervised Visual Pre-training
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training
Self-supervised learning (SSL) holds promise in leveraging large amounts of unlabeled data. However, the success of popular SSL methods has limited on single-centric-object images like those in ImageNet and ignores the correlation among the scene and instances, as well as the semantic difference of instances in the scene. To address …