2 code implementations • 23 Oct 2023 • Maomao Li, Ge Yuan, Cairong Wang, Zhian Liu, Yong Zhang, Yongwei Nie, Jue Wang, Dong Xu
Based on this disentanglement, face swapping can be simplified as style and mask swapping.
no code implementations • 28 Feb 2023 • Yunpeng Bai, Cairong Wang, Shuzhao Xie, Chao Dong, Chun Yuan, Zhi Wang
We use the text-image feature compatibility of the CLIP to alleviate the difficulty of fusing text and image features.
no code implementations • CVPR 2023 • Zhian Liu, Maomao Li, Yong Zhang, Cairong Wang, Qi Zhang, Jue Wang, Yongwei Nie
We rethink face swapping from the perspective of fine-grained face editing, \textit{i. e., ``editing for swapping'' (E4S)}, and propose a framework that is based on the explicit disentanglement of the shape and texture of facial components.
no code implementations • 7 Aug 2022 • Yunpeng Bai, Chao Dong, Cairong Wang
We study how to represent a video with implicit neural representations (INRs).
Ranked #5 on Video Reconstruction on UVG
no code implementations • 24 May 2022 • Yunpeng Bai, Cairong Wang, Chun Yuan, Yanbo Fan, Jue Wang
The content contrastive loss enables the encoder to retain more available details.