Search

Your search keyword '"Yan, Shuicheng"' showing total 31 results
Start Over Author "Yan, Shuicheng" Journal ieee transactions on multimedia
31 results on '"Yan, Shuicheng"'

7. Deep Relative Attributes

Author

Yang, Xiaoshan, primary, Zhang, Tianzhu, additional, Xu, Changsheng, additional, Yan, Shuicheng, additional, Hossain, M. Shamim, additional, and Ghoneim, Ahmed, additional

Published
2016
Full Text
View/download PDF

12. Scale-Aware Fast R-CNN for Pedestrian Detection.

Author

Li, Jianan, Liang, Xiaodan, Shen, Shengmei, Xu, Tingfa, Feng, Jiashi, and Yan, Shuicheng

Abstract

In this paper, we consider the problem of pedestrian detection in natural scenes. Intuitively, instances of pedestrians with different spatial scales may exhibit dramatically different features. Thus, large variance in instance scales, which results in undesirable large intracategory variance in features, may severely hurt the performance of modern object instance detection methods. We argue that this issue can be substantially alleviated by the divide-and-conquer philosophy. Taking pedestrian detection as an example, we illustrate how we can leverage this philosophy to develop a Scale-Aware Fast R-CNN (SAF R-CNN) framework. The model introduces multiple built-in subnetworks which detect pedestrians with scales from disjoint ranges. Outputs from all of the subnetworks are then adaptively combined to generate the final detection results that are shown to be robust to large variance in instance scales, via a gate function defined over the sizes of object proposals. Extensive evaluations on several challenging pedestrian detection datasets well demonstrate the effectiveness of the proposed SAF R-CNN. Particularly, our method achieves state-of-the-art performance on Caltech [P. Dollar, C. Wojek, B. Schiele, and P. Perona, “Pedestrian detection: An evaluation of the state of the art,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 4, pp. 743–761, Apr. 2012], and obtains competitive results on INRIA [N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2005, pp. 886–893], ETH [A. Ess, B. Leibe, and L. V. Gool, “Depth and appearance for mobile scene analysis,” in Proc. Int. Conf. Comput. Vis., 2007, pp. 1–8], and KITTI [A. Geiger, P. Lenz, and R. Urtasun, “Are we ready for autonomous driving? The KITTI vision benchmark suite,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2012, pp. 3354–3361]. [ABSTRACT FROM PUBLISHER]

Published
2018
Full Text
View/download PDF

14. Fashion Parsing With Video Context

Author

Liu, Si, primary, Liang, Xiaodan, additional, Liu, Luoqi, additional, Lu, Ke, additional, Lin, Liang, additional, Cao, Xiaochun, additional, and Yan, Shuicheng, additional

Published
2015
Full Text
View/download PDF

20. Image Re-Attentionizing

Author

Nguyen, Tam V., primary, Ni, Bingbing, additional, Liu, Hairong, additional, Xia, Wei, additional, Luo, Jiebo, additional, Kankanhalli, Mohan, additional, and Yan, Shuicheng, additional

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results