XMem++: Production-level Video Segmentation From Few Annotated Frames-Reference-Cited by-同舟云学术

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XMem++: Production-level Video Segmentation From Few Annotated Frames

Published:2023-10-01 Issue: Volume:34 Page:635-644
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Bekuzarov Maksym¹,Bermudez Ariana¹,Lee Joon-Young²,Li Hao¹

Affiliation:

1. MBZUAI

2. Adobe Research

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377980.pdf?arnumber=10377980

Reference48 articles.

1. BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video

2. Learning What to Learn for Video Object Segmentation

3. One-Shot Video Object Segmentation

4. XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model

5. Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cross-modal Spectral Fusion Model for Referring Video Object Segmentation;2024 IEEE 14th International Conference on Electronics Information and Emergency Communication (ICEIEC);2024-05-24

2. 3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking;International Journal of Computer Vision;2024-05-07

3. Learning the What and How of Annotation in Video Object Segmentation;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

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