MoNet : deep motion exploitation for video object segmentation

• المؤلفون الرئيسيون: Xiao, Huaxin, Feng, Jiashi, Lin, Guosheng, Liu, Yu, Zhang, Maojun
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Motion Segmentation; Feature Extraction
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/143257

In this paper, we propose a novel MoNet model to deeply exploit motion cues for boosting video object segmentation performance from two aspects, i.e., frame representation learning and segmentation refinement. Concretely, MoNet exploits computed motion cue (i.e., optical flow) to reinforce the repre...