N
Nanning Zheng
Researcher at Xi'an Jiaotong University
Publications - 773
Citations - 25602
Nanning Zheng is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Computer science & Object detection. The author has an hindex of 61, co-authored 722 publications receiving 20797 citations. Previous affiliations of Nanning Zheng include University of Sydney.
Papers
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Journal ArticleDOI
Learning to Detect a Salient Object
TL;DR: A set of novel features, including multiscale contrast, center-surround histogram, and color spatial distribution, are proposed to describe a salient object locally, regionally, and globally.
Journal ArticleDOI
Stereo matching using belief propagation
TL;DR: This paper formulate the stereo matching problem as a Markov network and solve it using Bayesian belief propagation to obtain the maximum a posteriori (MAP) estimation in the Markovnetwork.
Proceedings ArticleDOI
Person Re-identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Function
TL;DR: A novel multi-channel parts-based convolutional neural network model under the triplet framework for person re-identification that significantly outperforms many state-of-the-art approaches, including both traditional and deep network-based ones, on the challenging i-LIDS, VIPeR, PRID2011 and CUHK01 datasets.
Book ChapterDOI
Stereo Matching Using Belief Propagation
TL;DR: This paper forms the stereo matching problem as a Markov network consisting of three coupled Markov random fields, and obtains the maximum a posteriori (MAP) estimation in the Markovnetwork by applying a Bayesian belief propagation (BP) algorithm.
Proceedings ArticleDOI
Salient Object Detection: A Discriminative Regional Feature Integration Approach
TL;DR: This paper regards saliency map computation as a regression problem, which is based on multi-level image segmentation, and uses the supervised learning approach to map the regional feature vector to a saliency score, and finally fuses the saliency scores across multiple levels, yielding the salency map.