Reciprocal transformations for unsupervised video object segmentation

• Main Authors: REN, Sucheng, LIU, Wenxi, LIU, Yongtuo, CHEN, Haoxin, HAN, Guoqiang, HE, Shengfeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Computer vision; Image segmentation; Background objects; Flow informations; Human intervention; Key factors; Localisation; Motion cues; Motion features; Moving objects; Prior-knowledge; Video objects segmentations; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8441; https://ink.library.smu.edu.sg/context/sis_research/article/9444/viewcontent/Ren_Reciprocal_Transformations_for_Unsupervised_Video_Object_Segmentation_CVPR_2021_paper.pdf
• Institution: Singapore Management University

Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in videos without any human intervention. Due to the lack of prior knowledge about the primary objects, identifying them from videos is the major challenge of UVOS. Previous methods often regard the moving objects a...