Zobrazeno 1 - 10
of 386
pro vyhledávání: '"Zhang, Zhimeng"'
Autor:
Liu, Hanwei, An, Rudong, Zhang, Zhimeng, Ma, Bowen, Zhang, Wei, Song, Yan, Hu, Yujing, Chen, Wei, Ding, Yu
Facial Expression Analysis remains a challenging task due to unexpected task-irrelevant noise, such as identity, head pose, and background. To address this issue, this paper proposes a novel framework, called Norface, that is unified for both Action
Externí odkaz:
http://arxiv.org/abs/2407.15617
Autor:
Hong, Zhiqing, Huang, Rongjie, Cheng, Xize, Wang, Yongqi, Li, Ruiqi, You, Fuming, Zhao, Zhou, Zhang, Zhimeng
A song is a combination of singing voice and accompaniment. However, existing works focus on singing voice synthesis and music generation independently. Little attention was paid to explore song synthesis. In this work, we propose a novel task called
Externí odkaz:
http://arxiv.org/abs/2404.09313
Autor:
Fan, Wenru, Qi, Wei, Zhang, Jingli, Cao, Zongwei, Lan, Haoyang, Li, Xinxiang, Xu, Yi, Gu, Yuqiu, Deng, Zhigang, Zhang, Zhimeng, Tan, Changxiang, Luo, Wen, Yuan, Yun, Zhou, Weimin
Nuclear isomers play a key role in the creation of the elements in the universe and have a number of fascinating potential applications related to the controlled release of nuclear energy on demand. Particularly, $^{93m}$Mo isomer is a good candidate
Externí odkaz:
http://arxiv.org/abs/2308.02994
Autor:
Zhang, Yu, Zeng, Hao, Ma, Bowen, Zhang, Wei, Zhang, Zhimeng, Ding, Yu, Lv, Tangjie, Fan, Changjie
This work proposes a novel face-swapping framework FlowFace++, utilizing explicit semantic flow supervision and end-to-end architecture to facilitate shape-aware face-swapping. Specifically, our work pretrains a facial shape discriminator to supervis
Externí odkaz:
http://arxiv.org/abs/2306.12686
For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity dubbing results. To address the above problem, this paper proposes a Def
Externí odkaz:
http://arxiv.org/abs/2303.03988
Autor:
Zeng, Hao, Zhang, Wei, Fan, Changjie, Lv, Tangjie, Wang, Suzhen, Zhang, Zhimeng, Ma, Bowen, Li, Lincheng, Ding, Yu, Yu, Xin
In this work, we propose a semantic flow-guided two-stage framework for shape-aware face swapping, namely FlowFace. Unlike most previous methods that focus on transferring the source inner facial features but neglect facial contours, our FlowFace can
Externí odkaz:
http://arxiv.org/abs/2212.02797
Distinctive Image Captioning (DIC) -- generating distinctive captions that describe the unique details of a target image -- has received considerable attention over the last few years. A recent DIC work proposes to generate distinctive captions by co
Externí odkaz:
http://arxiv.org/abs/2207.11118
Unbiased SGG has achieved significant progress over recent years. However, almost all existing SGG models have overlooked the ground-truth annotation qualities of prevailing SGG datasets, i.e., they always assume: 1) all the manually annotated positi
Externí odkaz:
http://arxiv.org/abs/2206.03014
Reasoning about causal and temporal event relations in videos is a new destination of Video Question Answering (VideoQA).The major stumbling block to achieve this purpose is the semantic gap between language and video since they are at different leve
Externí odkaz:
http://arxiv.org/abs/2204.11544
Autor:
Zhang, Wei, Qiu, Feng, Wang, Suzhen, Zeng, Hao, Zhang, Zhimeng, An, Rudong, Ma, Bowen, Ding, Yu
Human affective behavior analysis has received much attention in human-computer interaction (HCI). In this paper, we introduce our submission to the CVPR 2022 Competition on Affective Behavior Analysis in-the-wild (ABAW). To fully exploit affective k
Externí odkaz:
http://arxiv.org/abs/2203.12367