Leveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking 事件

Leveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking arXiv:2605.26933v1 Announce Type: new Abstract: Unsupervised visual object tracking is a challenging task that requires following arbitrary targets in videos without training on ground-truth annotations. Despite considerable progress, existing state-of-the-art unsupervised trackers often struggle in scenarios that demand fine-grained understanding of semantic and visual structural information within video frames.