no code implementations • 13 Aug 2018 • Yatao Zhong, Bicheng Xu, Guang-Tong Zhou, Luke Bornn, Greg Mori
Numerous powerful point process models have been developed to understand temporal patterns in sequential data from fields such as health-care, electronic commerce, social networks, and natural disaster forecasting.
1 code implementation • 18 Feb 2018 • Nelson Nauata, Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng, Zicheng Liao, Greg Mori
In this paper, we exploit this rich structure for performing graph-based inference in label space for a number of tasks: multi-label image and video classification and action detection in untrimmed videos.
1 code implementation • 29 Mar 2017 • Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori
We advocate that holistic inference of image concepts provides valuable information for detailed pixel labeling.
no code implementations • 24 Nov 2016 • Hexiang Hu, Zhiwei Deng, Guang-Tong Zhou, Fei Sha, Greg Mori
We advocate that high-recall holistic inference of image concepts provides valuable information for detailed pixel labeling.
no code implementations • CVPR 2016 • Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng, Zicheng Liao, Greg Mori
Images of scenes have various objects as well as abundant attributes, and diverse levels of visual categorization are possible.
no code implementations • 12 Feb 2015 • Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou, Hossein Hajimirsadeghi, Mehrsan Javan Roshtkhari, Greg Mori, Stephen Se
We present a novel approach for discovering human interactions in videos.
no code implementations • 6 Feb 2015 • Guang-Tong Zhou, Sung Ju Hwang, Mark Schmidt, Leonid Sigal, Greg Mori
We present a hierarchical maximum-margin clustering method for unsupervised data analysis.
no code implementations • NeurIPS 2013 • Guang-Tong Zhou, Tian Lan, Arash Vahdat, Greg Mori
We present a maximum margin framework that clusters data using latent variables.
no code implementations • CVPR 2013 • Guang-Tong Zhou, Tian Lan, Weilong Yang, Greg Mori
We conduct image classification by learning a class-toimage distance function that matches objects.