Zobrazeno 1 - 10
of 301
pro vyhledávání: '"Sang, Shen"'
Autor:
Zhang, Yimeng, Zhi, Tiancheng, Liu, Jing, Sang, Shen, Jiang, Liming, Yan, Qing, Liu, Sijia, Luo, Linjie
The ability to synthesize personalized group photos and specify the positions of each identity offers immense creative potential. While such imagery can be visually appealing, it presents significant challenges for existing technologies. A persistent
Externí odkaz:
http://arxiv.org/abs/2411.13632
Portrait editing is challenging for existing techniques due to difficulties in preserving subject features like identity. In this paper, we propose a training-based method leveraging auto-generated paired data to learn desired editing while ensuring
Externí odkaz:
http://arxiv.org/abs/2407.20455
Publikováno v:
In Journal of Traditional and Complementary Medicine January-March 2013 3(1):7-15
Autor:
Yin, Yufeng, Chang, Di, Song, Guoxian, Sang, Shen, Zhi, Tiancheng, Liu, Jing, Luo, Linjie, Soleymani, Mohammad
Automatic detection of facial Action Units (AUs) allows for objective facial expression analysis. Due to the high cost of AU labeling and the limited size of existing benchmarks, previous AU detection methods tend to overfit the dataset, resulting in
Externí odkaz:
http://arxiv.org/abs/2308.12380
While NeRF-based human representations have shown impressive novel view synthesis results, most methods still rely on a large number of images / views for training. In this work, we propose a novel animatable NeRF called ActorsNeRF. It is first pre-t
Externí odkaz:
http://arxiv.org/abs/2304.14401
Autor:
Song, Guoxian, Xu, Hongyi, Liu, Jing, Zhi, Tiancheng, Shi, Yichun, Zhang, Jianfeng, Jiang, Zihang, Feng, Jiashi, Sang, Shen, Luo, Linjie
While substantial progresses have been made in automated 2D portrait stylization, admirable 3D portrait stylization from a single user photo remains to be an unresolved challenge. One primary obstacle here is the lack of high quality stylized 3D trai
Externí odkaz:
http://arxiv.org/abs/2303.14297
Avatar creation from human images allows users to customize their digital figures in different styles. Existing rendering systems like Bitmoji, MetaHuman, and Google Cartoonset provide expressive rendering systems that serve as excellent design tools
Externí odkaz:
http://arxiv.org/abs/2302.07354
Autor:
Sang, Shen, Zhi, Tiancheng, Song, Guoxian, Liu, Minghao, Lai, Chunpong, Liu, Jing, Wen, Xiang, Davis, James, Luo, Linjie
Stylized 3D avatars have become increasingly prominent in our modern life. Creating these avatars manually usually involves laborious selection and adjustment of continuous and discrete parameters and is time-consuming for average users. Self-supervi
Externí odkaz:
http://arxiv.org/abs/2211.07818
Autor:
Li, Zhengqin, Yu, Ting-Wei, Sang, Shen, Wang, Sarah, Song, Meng, Liu, Yuhan, Yeh, Yu-Ying, Zhu, Rui, Gundavarapu, Nitesh, Shi, Jia, Bi, Sai, Xu, Zexiang, Yu, Hong-Xing, Sunkavalli, Kalyan, Hašan, Miloš, Ramamoorthi, Ravi, Chandraker, Manmohan
We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics. Our goal is to make the dataset creation process widely accessible, transforming scans into
Externí odkaz:
http://arxiv.org/abs/2007.12868
Autor:
Sang, Shen, Zhuang, Xinshu, Chen, Haiyan, Qin, Yuyue, Cao, Jianxin, Fan, Fangling, Lan, Tianqing
Publikováno v:
In Industrial Crops & Products June 2022 180