Match4Annotate: Propagating Sparse Video Annotations via Implicit Neural Feature Matching

ArXi:2603.06471v1 Announce Type: new Acquiring per-frame video annotations remains a primary bottleneck for deploying computer vision in specialized domains such as medical imaging, where expert labeling is slow and costly. Label propagation offers a natural solution, yet existing approaches face fundamental limitations. Video trackers and segmentation models can propagate labels within a single sequence but require per-video initialization and cannot generalize across videos.