Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Xiaohui Shen"'
Autor:
Radomir Mech, Jianming Zhang, Minh Hoai, Zijun Wei, Boyu Wang, Xiaohui Shen, Dimitris Samaras, Zhe Lin
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 43:1009-1021
Detecting segments of interest from videos is a common problem for many applications. And yet it is a challenging problem as it often requires not only knowledge of individual target segments, but also contextual understanding of the entire video and
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 50:707-716
Power demand side management (DSM) regulations stipulate that electric power grid enterprises of cities and provinces must complete their target of power saving through efficient power plant (EPP) programs. This investigation studies power DSM and es
Autor:
Xiaohui Shen, Wei Yan
Publikováno v:
Advances in Social Science, Education and Humanities Research.
Publikováno v:
3DV
Recently, significant progress has been made in single-view depth estimation thanks to increasingly large and diverse depth datasets. However, these datasets are largely limited to specific application domains (e.g. indoor, autonomous driving) or sta
Autor:
Xiaodan Liang, Xujie Zhang, Xiaohui Shen, Jian Yin, Zhenyu Xie, Yixuan Zhang, Bowen Wu, Haoye Dong
Publikováno v:
CVPR
Interactive fashion image manipulation, which enables users to edit images with sketches and color strokes, is an interesting research problem with great application value. Existing works often treat it as a general inpainting task and do not fully l
Publikováno v:
WACV
People usually take short videos to record meaningful moments in their lives. However, selecting the most representative frame, which not only has high image visual quality but also captures video content, from a short video to share or keep is a tim
In this work, we propose a new solution to 3D human pose estimation in videos. Instead of directly regressing the 3D joint locations, we draw inspiration from the human skeleton anatomy and decompose the task into bone direction prediction and bone l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab565e9d260919923de802a9f974cec4
http://arxiv.org/abs/2002.10322
http://arxiv.org/abs/2002.10322
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030586201
ECCV (11)
ECCV (11)
This paper focuses on learning transferable adversarial examples specifically against defense models (models to defense adversarial attacks). In particular, we show that a simple universal perturbation can fool a series of state-of-the-art defenses.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a961631e17645585fa587c2ba404b0d7
https://doi.org/10.1007/978-3-030-58621-8_46
https://doi.org/10.1007/978-3-030-58621-8_46
Publikováno v:
Computer Vision – ECCV 2020 Workshops ISBN: 9783030670696
ECCV Workshops (3)
ECCV Workshops (3)
In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video. It is a video-to-video translation task in which the estimated poses are used
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74886a49fd6b6e552286fb4b2d0b371b
https://doi.org/10.1007/978-3-030-67070-2_16
https://doi.org/10.1007/978-3-030-67070-2_16
Autor:
Jing Liu, Xiaohui Shen, Jun Liu, Yiheng Zhu, Junsong Yuan, Yujun Cai, Ding Liu, Lin Huang, Nadia Magnenat Thalmann, Jianfei Cai, Yiwei Wang, Tat-Jen Cham, Xu Yang
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585709
ECCV (7)
ECCV (7)
Despite the great progress in human motion prediction, it remains a challenging task due to the complicated structural dynamics of human behaviors. In this paper, we address this problem in three aspects. First, to capture the long-range spatial corr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b31acc462f597cdfd89519de4440d362
https://doi.org/10.1007/978-3-030-58571-6_14
https://doi.org/10.1007/978-3-030-58571-6_14