AvatarFusion: Zero-shot Generation of Clothing-Decoupled 3D Avatars Using 2D Diffusion-Reference-Cited by-同舟云学术

AvatarFusion: Zero-shot Generation of Clothing-Decoupled 3D Avatars Using 2D Diffusion

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Huang Shuo¹^ORCID,Yang Zongxin²^ORCID,Li Liangting¹^ORCID,Yang Yi²^ORCID,Jia Jia³^ORCID

Affiliation:

1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

2. ReLER, CCAI, Zhejiang University, Zhejiang, China

3. Department of Computer Science and Technology, Tsinghua University & Beijing National Research Center for Information Science and Technology, Beijing, China

Funder

This work is supported by the National Key R&D Program of China under Grant No. 2021QY1500, the State Key Program of the National Natural Science Foundation of China (NSFC) (No.61831022).

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612022

Reference56 articles.

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3. Yangming Cheng , Liulei Li , Yuanyou Xu , Xiaodi Li , Zongxin Yang , Wenguan Wang , and Yi Yang . 2023. Segment and track anything. arXiv preprint arXiv:2305.06558 ( 2023 ). Yangming Cheng, Liulei Li, Yuanyou Xu, Xiaodi Li, Zongxin Yang, Wenguan Wang, and Yi Yang. 2023. Segment and track anything. arXiv preprint arXiv:2305.06558 (2023).

4. SMPLicit: Topology-aware Generative Model for Clothed People

5. Decoupling Zero-Shot Semantic Segmentation

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