Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Jingen Liu"'
Publikováno v:
ACM Computing Surveys. 55:1-46
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment of various systems based on it. However, many current AI systems are found vulnerable to imperceptible attacks, biased against underrepresented groups, lackin
Autor:
Philip H. S. Torr, Haitao Zhang, Bin Yan, Ziyi Cheng, Fahad Shahbaz Khan, Shoumeng Qiu, Bineng Zhong, Ondrej Drbohlav, Bo Liu, Ozgun Cirakman, Kristian Simonato, Danda Pani Paudel, Xin Chen, Xiangyuan Lan, Wei Lu, Martin Danelljan, Felix Järemo Lawin, Qing Guo, Luka Čehovin Zajc, Christoph Mayer, Xiao Ke, Wankou Yang, Yanyan Huang, Xiaoning Song, Dong Wang, Felix Juefei-Xu, Xue-Feng Zhu, Guangting Wang, Jingen Liu, Jani Käpylä, Ales Leonardis, Christian Micheloni, Paul Voigtlaender, Yu-Chen Chiu, Lijun Wang, Shengyong Chen, Linyuan Wang, Shaochuan Zhao, Ling Shao, Yong Wang, Li Liu, Xiaoyun Yang, Liangliang Wang, Rongrong Ji, Gustavo Fernandez, Bilge Gunsel, Xingping Dong, Fei Xie, Jun Yin, Zhangyong Tang, Michael Felsberg, Aravindh Rajiv, Andreas Robinson, Miao Cheng, Mohana Murali Dasari, Josef Kittler, Chang Liu, Wencheng Han, Zhongqun Zhang, Yuezhou Li, Bedirhan Uzun, Roman Pflugfelder, Jinyu Yang, Yu Ye, Goutam Bhat, Kangkai Zhang, Hui Li, Jiri Matas, Mohamed H. Abdelpakey, Zhen-Hua Feng, Hyung Jin Chang, Ming Zhen, Matteo Dunnhofer, Xianxian Li, Yingjie Jiang, Luc Van Gool, Matej Kristan, Xiang Xu, Bastian Leibe, Xinyu Zhang, Filiz Gurkan, Jun Ha Lee, Yunhong Wang, Niki Martinel, Shang-Jhih Jhang, Yin Jun, Jianhua Li, Chengwei Zhang, Cheng Jiang, Muhammad Rana, Jie Ma, Houwen Peng, Gustav Häger, Zhiyong Feng, Wanli Xue, Gangshan Wu, Joni-Kristian Kamarainen, Zhibin Zhang, Alireza Memarmoghadam, Qili Deng, Daniel K. Du, Shiming Ge, Mohamed Shehata, Zhihong Fu, Chunhui Zhang, Yuzhen Niu, Xiaojun Wu, Rama Krishna Sai Subrahmanyam Gorthi, Hasan Saribas, Yuzhang Gu, Kenan Dai, Furao Shen, Qingjie Liu, Byeong Hak Kim, Hakan Cevikalp, Llukman Cerkezi, Jianbing Shen, Chenyan Wu, Alan Lukezic, Jiawen Zhu, Ziang Ma, Xiaohan Zhang, Limin Wang, Radu Timofte, Chi-Yi Tsai, Song Yan, Jonathon Luiten, Huchuan Lu, Kaihua Zhang, Tianyang Xu, Yutao Cui, Xiaolin Zhang
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::717763c198da14f9ea29d111bbb1d71f
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
https://ora.ox.ac.uk/objects/uuid:d4585a6f-2205-4f68-b34a-8b6a61758cc8
Publikováno v:
IEEE Transactions on Medical Imaging. 39:2904-2919
Vascular tree disentanglement and vessel type classification are two crucial steps of the graph-based method for retinal artery-vein (A/V) separation. Existing approaches treat them as two independent tasks and mostly rely on ad hoc rules (e.g. chang
In this study, we aim to predict the plausible future action steps given an observation of the past and study the task of instructional activity anticipation. Unlike previous anticipation tasks that aim at action label prediction, our work targets at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9abb9b19fefd2723503eb477971f8722
http://arxiv.org/abs/2201.06734
http://arxiv.org/abs/2201.06734
Publikováno v:
ACM Multimedia
In this workshop, we are addressing the trustworthy AI issues for Multimedia Computing. We aim to bring together researchers in the trustworthy aspects of Multimedia Computing and facilitate discussions in injecting trusts into multimedia to develop
Publikováno v:
CVPR
Weakly supervised temporal action localization aims to detect and localize actions in untrimmed videos with only video-level labels during training. However, without frame-level annotations, it is challenging to achieve localization completeness and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9674efd2d63bac9933080271099ceb7
Publikováno v:
CVPR
Virtual try-on methods aim to generate images of fashion models wearing arbitrary combinations of garments. This is a challenging task because the generated image must appear realistic and accurately display the interaction between garments. Prior wo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db9301ab5eff7d65c37ea74a6a088b70
In this paper, we propose a novel video super-resolution method that aims at generating high-fidelity high-resolution (HR) videos from low-resolution (LR) ones. Previous methods predominantly leverage temporal neighbor frames to assist the super-reso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71cd744b254700f8e1691583969f2a89
Some cognitive research has discovered that humans accomplish event segmentation as a side effect of event anticipation. Inspired by this discovery, we propose a simple yet effective end-to-end self-supervised learning framework for event segmentatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7bcbf9715192ce1dc12bfaff0b44f66
Publikováno v:
ACM Multimedia
Real-time in-match soccer statistics provide continuous tracking of soccer ball and player positions and speeds, enabling advanced analytics. Currently, only elite soccer leagues have the luxury of tracking in-match soccer statistics operated with a