Exploring Memory Aggregation Networks For Efficient Interactive Video Object Segmentation
Exploring Memory Aggregation Networks For Efficient Interactive Video Object Segmentation reveals several interesting facts.
- Paper(arXiv) - https://arxiv.org/abs/2104.10386 Github - https://github.com/yuk6heo/GIS-RAmap.
- A description and demo of our work for
- Paper(arXiv) - https://arxiv.org/abs/2104.10386 Github - https://github.com/yuk6heo/GIS-RAmap.
- Learn all the ways Microsoft is a part of CVPR 2020: https://www.microsoft.com/en-us/research/event/cvpr-2020/
- Authors: Lee, Minhyeok*; Cho, Suhwan; LEE, SEUNGHOON; Park, Chaewon; Lee, Sangyoun Description: Unsupervised
In-Depth Information on Memory Aggregation Networks For Efficient Interactive Video Object Segmentation
Authors: Jiaxu Miao, Yunchao Wei, Yi Yang Description: TITLE: ICCV17 | 1148 | Learning The spotlight video for
Learning What to Learn for Video Object Segmentation: ECCV2020 Oral, Long video
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