Surface-SOS: Self-Supervised Object Segmentation via Neural Surface Representation
Author:
Affiliation:
1. School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
2. School of Computer Science, University of Birmingham, Birmingham, U.K
3. School of Arts, Peking University, Beijing, China
Funder
Outstanding Talents Training Fund in Shenzhen
Shenzhen Science and Technology Program-Shenzhen Cultivation of Excellent Scientific and Technological Innovation Talents Project
Shenzhen Science and Technology Program-Shenzhen Hong Kong Joint
National Natural Science Foundation of China
Migu Cultural Technology Company Ltd., (Migu)-Peking University Meta Vision Technology Innovation Laboratory
Royal Society
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/83/10346232/10471326.pdf?arnumber=10471326
Reference60 articles.
1. Multi-view Object Segmentation in Space and Time
2. MATNet: Motion-Attentive Transition Network for Zero-Shot Video Object Segmentation
3. Editable free-viewpoint video using a layered neural representation
4. Control-NeRF: Editable Feature Volumes for Scene Rendering and Manipulation
5. Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering
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