Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Xiaohui Shen"'
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:
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:
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
Publikováno v:
ICCV
Deep CNNs have been pushing the frontier of visual recognition over past years. Besides recognition accuracy, strong demands in understanding deep CNNs in the research community motivate developments of tools to dissect pre-trained models to visualiz
Autor:
Jianchao Yang, Shuicheng Yan, Chunyan Xu, Jinhui Tang, Xiaodan Liang, Liang Lin, Xiaohui Shen
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 39:115-127
In this work, we address the human parsing task with a novel Contextualized Convolutional Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global image-level context, semantic edge context, within-super-pixel conte
Autor:
Ding Liu, Yu Cheng, Xiaohui Shen, Chen Fang, Pan Zhou, Yifan Jiang, Jianchao Yang, Zhangyang Wang, Xinyu Gong
Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As one such example, this paper explores the low-light image enhancement p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1c517bcc236be77e3d9e8c67b9e169e
http://arxiv.org/abs/1906.06972
http://arxiv.org/abs/1906.06972
Publikováno v:
CVPR
Prior highly-tuned human parsing models tend to fit towards each dataset in a specific domain or with discrepant label granularity, and can hardly be adapted to other human parsing tasks without extensive re-training. In this paper, we aim to learn a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec37fe558c45896dcc49885299a73a18
http://arxiv.org/abs/1904.04536
http://arxiv.org/abs/1904.04536
Publikováno v:
IEEE Transactions on Image Processing. 24:3321-3331
In this paper, we propose a novel adaptive metric learning algorithm (AML) for visual saliency detection. A key observation is that the saliency of a superpixel can be estimated by the distance from the most certain foreground and background seeds. I
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 40(12)
Instance-level object segmentation is an important yet under-explored task. The few existing studies are almost all based on region proposal methods to extract candidate segments and then utilize object classification to produce final results. Noneth