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pro vyhledávání: '"Xiong, Zhangyang"'
Autor:
Xiong, Zhangyang, Li, Chenghong, Liu, Kenkun, Liao, Hongjie, Hu, Jianqiao, Zhu, Junyi, Ning, Shuliang, Qiu, Lingteng, Wang, Chongjie, Wang, Shijie, Cui, Shuguang, Han, Xiaoguang
In this era, the success of large language models and text-to-image models can be attributed to the driving force of large-scale datasets. However, in the realm of 3D vision, while remarkable progress has been made with models trained on large-scale
Externí odkaz:
http://arxiv.org/abs/2312.02963
Autor:
Yu, Xianggang, Xu, Mutian, Zhang, Yidan, Liu, Haolin, Ye, Chongjie, Wu, Yushuang, Yan, Zizheng, Zhu, Chenming, Xiong, Zhangyang, Liang, Tianyou, Chen, Guanying, Cui, Shuguang, Han, Xiaoguang
Being data-driven is one of the most iconic properties of deep learning algorithms. The birth of ImageNet drives a remarkable trend of "learning from large-scale data" in computer vision. Pretraining on ImageNet to obtain rich universal representatio
Externí odkaz:
http://arxiv.org/abs/2303.06042
Autor:
Xiong, Zhangyang, Kang, Di, Jin, Derong, Chen, Weikai, Bao, Linchao, Cui, Shuguang, Han, Xiaoguang
Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiable rendering have enabled the training of 3D generative models without
Externí odkaz:
http://arxiv.org/abs/2302.01162
Autor:
Xiong, Zhangyang, Du, Dong, Wu, Yushuang, Dong, Jingqi, Kang, Di, Bao, Linchao, Han, Xiaoguang
It is very challenging to accurately reconstruct sophisticated human geometry caused by various poses and garments from a single image. Recently, works based on pixel-aligned implicit function (PIFu) have made a big step and achieved state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2208.10769
In this paper we examine the problem of inverse rendering of real face images. Existing methods decompose a face image into three components (albedo, normal, and illumination) by supervised training on synthetic face data. However, due to the domain
Externí odkaz:
http://arxiv.org/abs/2003.12047
Autor:
Wang, Zhongyuan, Wang, Guangcheng, Huang, Baojin, Xiong, Zhangyang, Hong, Qi, Wu, Hao, Yi, Peng, Jiang, Kui, Wang, Nanxi, Pei, Yingjiao, Chen, Heling, Miao, Yu, Huang, Zhibing, Liang, Jinbi
In order to effectively prevent the spread of COVID-19 virus, almost everyone wears a mask during coronavirus epidemic. This almost makes conventional facial recognition technology ineffective in many cases, such as community access control, face acc
Externí odkaz:
http://arxiv.org/abs/2003.09093
Publikováno v:
Advances in Multimedia Information Processing – PCM 2018 ISBN: 9783030007669
PCM (2)
PCM (2)
The face recognition scheme based on deep learning can give the best face recognition performance at present, but this scheme requires a large amount of labeled face data. The currently available large-scale face datasets are mainly Westerners, only
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e998c888cbe76bc15785d054b63d05f
https://doi.org/10.1007/978-3-030-00767-6_35
https://doi.org/10.1007/978-3-030-00767-6_35
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