Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Li, Moran"'
Publikováno v:
International Conference on Machine Learning (ICML), 2024
We aim to address Multi-Task Learning (MTL) with a large number of tasks by Multi-Task Grouping (MTG). Given N tasks, we propose to simultaneously identify the best task groups from 2^N candidates and train the model weights simultaneously in one-sho
Externí odkaz:
http://arxiv.org/abs/2407.05082
Autor:
Hao, Jinkun, Tang, Junshu, Zhang, Jiangning, Yi, Ran, Hong, Yijia, Li, Moran, Cao, Weijian, Wang, Yating, Ma, Lizhuang
While recent works have achieved great success on one-shot 3D common object generation, high quality and fidelity 3D head generation from a single image remains a great challenge. Previous text-based methods for generating 3D heads were limited by te
Externí odkaz:
http://arxiv.org/abs/2406.16710
Autor:
Fan, Ke, Tang, Junshu, Cao, Weijian, Yi, Ran, Li, Moran, Gong, Jingyu, Zhang, Jiangning, Wang, Yabiao, Wang, Chengjie, Ma, Lizhuang
Text-to-motion synthesis is a crucial task in computer vision. Existing methods are limited in their universality, as they are tailored for single-person or two-person scenarios and can not be applied to generate motions for more individuals. To achi
Externí odkaz:
http://arxiv.org/abs/2405.15763
Autor:
Wang, Sen, Zhang, Jiangning, Cao, Weijian, Hu, Xiaobin, Li, Moran, Ji, Xiaozhong, Tan, Xin, Li, Mengtian, Xie, Zhifeng, Wang, Chengjie, Ma, Lizhuang
The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion, generatin
Externí odkaz:
http://arxiv.org/abs/2403.02905
Autor:
Zheng, Yujian, Jin, Zirong, Li, Moran, Huang, Haibin, Ma, Chongyang, Cui, Shuguang, Han, Xiaoguang
In this work, we tackle the challenging problem of learning-based single-view 3D hair modeling. Due to the great difficulty of collecting paired real image and 3D hair data, using synthetic data to provide prior knowledge for real domain becomes a le
Externí odkaz:
http://arxiv.org/abs/2303.02700
In this work, we present a new method for 3D face reconstruction from sparse-view RGB images. Unlike previous methods which are built upon 3D morphable models (3DMMs) with limited details, we leverage an implicit representation to encode rich geometr
Externí odkaz:
http://arxiv.org/abs/2112.02494
In this paper, we propose to estimate 3D hand pose by recovering the 3D coordinates of joints in a group-wise manner, where less-related joints are automatically categorized into different groups and exhibit different features. This is different from
Externí odkaz:
http://arxiv.org/abs/2012.09496
Akademický článek
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Publikováno v:
In Graphical Models May 2023 127
Akademický článek
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