Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Jiang, Zihang"'
With the recent advancements in single-image-based human mesh recovery, there is a growing interest in enhancing its performance in certain extreme scenarios, such as occlusion, while maintaining overall model accuracy. Although obtaining accurately
Externí odkaz:
http://arxiv.org/abs/2403.12473
Autor:
Lai, Haoran, Yao, Qingsong, Jiang, Zihang, Wang, Rongsheng, He, Zhiyang, Tao, Xiaodong, Zhou, S. Kevin
The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment. However, existing methods primarily rely on cosine similarity for align
Externí odkaz:
http://arxiv.org/abs/2402.17417
Autor:
Wang, Rongsheng, Yao, Qingsong, Lai, Haoran, He, Zhiyang, Tao, Xiaodong, Jiang, Zihang, Zhou, S. Kevin
Despite significant advancements in medical vision-language pre-training, existing methods have largely overlooked the inherent entity-specific context within radiology reports and the complex cross-modality contextual relationships between text and
Externí odkaz:
http://arxiv.org/abs/2312.13316
Autor:
Gong, Kehong, Lian, Dongze, Chang, Heng, Guo, Chuan, Jiang, Zihang, Zuo, Xinxin, Mi, Michael Bi, Wang, Xinchao
We propose a novel task for generating 3D dance movements that simultaneously incorporate both text and music modalities. Unlike existing works that generate dance movements using a single modality such as music, our goal is to produce richer dance m
Externí odkaz:
http://arxiv.org/abs/2304.02419
Autor:
Xu, Hongyi, Song, Guoxian, Jiang, Zihang, Zhang, Jianfeng, Shi, Yichun, Liu, Jing, Ma, Wanchun, Feng, Jiashi, Luo, Linjie
We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control ov
Externí odkaz:
http://arxiv.org/abs/2303.15539
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
Autor:
Zhang, Jianfeng, Jiang, Zihang, Yang, Dingdong, Xu, Hongyi, Shi, Yichun, Song, Guoxian, Xu, Zhongcong, Wang, Xinchao, Feng, Jiashi
Unsupervised generation of 3D-aware clothed humans with various appearances and controllable geometries is important for creating virtual human avatars and other AR/VR applications. Existing methods are either limited to rigid object modeling, or not
Externí odkaz:
http://arxiv.org/abs/2211.14589
Autor:
He, Yuzhou, Zhang, Jicheng, Jiang, Zihang, Zhou, Bowen, Zheng, Zezhong, Wang, Yifan, Lu, Qichao, Huang, Wenjie
Publikováno v:
In Composites Communications October 2024 50
Autor:
Shi, Yujun, Zhou, Kuangqi, Liang, Jian, Jiang, Zihang, Feng, Jiashi, Torr, Philip, Bai, Song, Tan, Vincent Y. F.
Class Incremental Learning (CIL) aims at learning a multi-class classifier in a phase-by-phase manner, in which only data of a subset of the classes are provided at each phase. Previous works mainly focus on mitigating forgetting in phases after the
Externí odkaz:
http://arxiv.org/abs/2112.04731
Autor:
Jiang, Zihang, Xiao, Yu, Xu, Zhengyao, Gu, Zhengbiao, Li, Zhaofeng, Ban, Xiaofeng, Hong, Yan, Cheng, Li, Li, Caiming
Publikováno v:
In Carbohydrate Polymers 1 December 2024 345