Self-supervised Video Object Segmentation with Distillation Learning of Deformable Attention

arXiv:2401.13937v2 Announce Type: replace
Abstract: Video object segmentation is a fundamental research problem in computer vision. Recent techniques have often applied attention mechanism to object representation learning from video sequences. However, due to temporal changes in the video data, attention maps may not well align with the objects of interest across video frames, causing accumulated errors in long-term video processing. In addition, existing techniques have utilised complex architectures, requiring highly computational complexity and hence limiting the ability to integrate video …

abstract arxiv attention computer computer vision cs.cv data distillation however maps object objects representation representation learning research segmentation temporal type video video data vision