Zobrazeno 1 - 10
of 529
pro vyhledávání: '"Li Songnan"'
Autor:
Tang, Xiangjun, Wu, Linjun, Wang, He, Wu, Yiqian, Hu, Bo, Li, Songnan, Gong, Xu, Liao, Yuchen, Kou, Qilong, Jin, Xiaogang
Motion style transfer changes the style of a motion while retaining its content and is useful in computer animations and games. Contact is an essential component of motion style transfer that should be controlled explicitly in order to express the st
Externí odkaz:
http://arxiv.org/abs/2409.05387
Autor:
Tang, Xiangjun, Wu, Linjun, Wang, He, Hu, Bo, Gong, Xu, Liao, Yuchen, Li, Songnan, Kou, Qilong, Jin, Xiaogang
Publikováno v:
SIGGRAPH 2023 Conference Proceedings
Styled online in-between motion generation has important application scenarios in computer animation and games. Its core challenge lies in the need to satisfy four critical requirements simultaneously: generation speed, motion quality, style diversit
Externí odkaz:
http://arxiv.org/abs/2306.11970
Recently, high-quality video conferencing with fewer transmission bits has become a very hot and challenging problem. We propose FAIVConf, a specially designed video compression framework for video conferencing, based on the effective neural human fa
Externí odkaz:
http://arxiv.org/abs/2207.04090
Publikováno v:
In International Journal of Biological Macromolecules October 2024 278 Part 3
Publikováno v:
In International Journal of Biological Macromolecules October 2024 278 Part 1
Autor:
Qing, Shiqin, Weng, Wuyin, Dai, Yaolin, Li, Ping, Ren, Zhongyang, Zhang, Yucang, Shi, Linfan, Li, Songnan
Publikováno v:
In International Journal of Biological Macromolecules October 2024 277 Part 1
Publikováno v:
In Renewable Energy September 2024 231
Publikováno v:
In Carbohydrate Polymers 1 January 2025 347
Autor:
Huang, Xuerong, Zhao, Feng, Teng, Zifan, Li, Yingkai, Zhang, Chuang, Liu, Xingxun, Li, Songnan, Xie, Fengwei
Publikováno v:
In Food Hydrocolloids January 2025 158
Publikováno v:
CVPRW on NTIRE 2022
This work addresses two major issues of end-to-end learned image compression (LIC) based on deep neural networks: variable-rate learning where separate networks are required to generate compressed images with varying qualities, and the train-test mis
Externí odkaz:
http://arxiv.org/abs/2111.08256