Zobrazeno 1 - 10
of 938
pro vyhledávání: '"WU, Xiaofei"'
Effectively modeling the interaction between human hands and objects is challenging due to the complex physical constraints and the requirement for high generation efficiency in applications. Prior approaches often employ computationally intensive tw
Externí odkaz:
http://arxiv.org/abs/2411.14786
Autor:
He, Qianyun, Ji, Xinya, Gong, Yicheng, Lu, Yuanxun, Diao, Zhengyu, Huang, Linjia, Yao, Yao, Zhu, Siyu, Ma, Zhan, Xu, Songcen, Wu, Xiaofei, Zhang, Zixiao, Cao, Xun, Zhu, Hao
We present a novel approach for synthesizing 3D talking heads with controllable emotion, featuring enhanced lip synchronization and rendering quality. Despite significant progress in the field, prior methods still suffer from multi-view consistency a
Externí odkaz:
http://arxiv.org/abs/2408.00297
Distributed model fitting refers to the process of fitting a mathematical or statistical model to the data using distributed computing resources, such that computing tasks are divided among multiple interconnected computers or nodes, often organized
Externí odkaz:
http://arxiv.org/abs/2406.00703
Autor:
Liu, Jiayue, Tang, Xiao, Cheng, Freeman, Yang, Roy, Li, Zhihao, Liu, Jianzhuang, Huang, Yi, Lin, Jiaqi, Liu, Shiyong, Wu, Xiaofei, Xu, Songcen, Yuan, Chun
3D Gaussian Splatting showcases notable advancements in photo-realistic and real-time novel view synthesis. However, it faces challenges in modeling mirror reflections, which exhibit substantial appearance variations from different viewpoints. To tac
Externí odkaz:
http://arxiv.org/abs/2405.11921
Autor:
He, Xu, Huang, Qiaochu, Zhang, Zhensong, Lin, Zhiwei, Wu, Zhiyong, Yang, Sicheng, Li, Minglei, Chen, Zhiyi, Xu, Songcen, Wu, Xiaofei
Co-speech gestures, if presented in the lively form of videos, can achieve superior visual effects in human-machine interaction. While previous works mostly generate structural human skeletons, resulting in the omission of appearance information, we
Externí odkaz:
http://arxiv.org/abs/2404.01862
Autor:
Lin, Jiaqi, Li, Zhihao, Tang, Xiao, Liu, Jianzhuang, Liu, Shiyong, Liu, Jiayue, Lu, Yangdi, Wu, Xiaofei, Xu, Songcen, Yan, Youliang, Yang, Wenming
Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large scenes poses c
Externí odkaz:
http://arxiv.org/abs/2402.17427
Autor:
Liu, Yumeng, Yang, Yaxun, Wang, Youzhuo, Wu, Xiaofei, Wang, Jiamin, Yao, Yichen, Schwertfeger, Sören, Yang, Sibei, Wang, Wenping, Yu, Jingyi, He, Xuming, Ma, Yuexin
In this paper, we introduce RealDex, a pioneering dataset capturing authentic dexterous hand grasping motions infused with human behavioral patterns, enriched by multi-view and multimodal visual data. Utilizing a teleoperation system, we seamlessly s
Externí odkaz:
http://arxiv.org/abs/2402.13853
Autor:
Luo, Yin, Kong, Qingchao, Xu, Nan, Cao, Jia, Hao, Bao, Qu, Baoyu, Chen, Bo, Zhu, Chao, Zhao, Chenyang, Zhang, Donglei, Feng, Fan, Zhao, Feifei, Sun, Hailong, Yang, Hanxuan, Pan, Haojun, Liu, Hongyu, Guo, Jianbin, Du, Jiangtao, Wang, Jingyi, Li, Junfeng, Sun, Lei, Liu, Liduo, Dong, Lifeng, Liu, Lili, Wang, Lin, Zhang, Liwen, Wang, Minzheng, Wang, Pin, Yu, Ping, Li, Qingxiao, Yan, Rui, Zou, Rui, Li, Ruiqun, Huang, Taiwen, Wang, Xiaodong, Wu, Xiaofei, Peng, Xin, Zhang, Xina, Fang, Xing, Xiao, Xinglin, Hao, Yanni, Dong, Yao, Wang, Yigang, Liu, Ying, Jiang, Yongyu, Wang, Yungan, Wang, Yuqi, Wang, Zhangsheng, Yu, Zhaoxin, Luo, Zhen, Mao, Wenji, Wang, Lei, Zeng, Dajun
As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artific
Externí odkaz:
http://arxiv.org/abs/2312.14862
Autor:
Zhang, Haodong, Chen, ZhiKe, Xu, Haocheng, Hao, Lei, Wu, Xiaofei, Xu, Songcen, Zhang, Zhensong, Wang, Yue, Xiong, Rong
Capturing and preserving motion semantics is essential to motion retargeting between animation characters. However, most of the previous works neglect the semantic information or rely on human-designed joint-level representations. Here, we present a
Externí odkaz:
http://arxiv.org/abs/2312.01964
The parallel alternating direction method of multipliers (ADMM) algorithm is widely recognized for its effectiveness in handling large-scale datasets stored in a distributed manner, making it a popular choice for solving statistical learning models.
Externí odkaz:
http://arxiv.org/abs/2311.12319