Welcome to Jialue Fan's Website

Fan, Jialue

Ph.D

@Knossos, Greece, 2010

Jialue Fan received the B.E and M.S. degree from Electrical Engineering at Tsinghua University, P.R.China in 2005 and 2007 respectively, and the Ph.D. degree from Department of EECS at Northwestern University in 2011 (advisor: Prof. Ying Wu). His research interests include computer vision and image/video processing. His Ph.D. thesis focuses on visual tracking.

He was with Adobe Systems Incorporated, CA (summer 2010), Siemens Corporate Research, NJ (summer 2009), and NEC Laboratories America, Inc., CA (summer 2008), respectively. He serves as a reviewer for premium academic conferences (e.g., ICCV, CVPR, ECCV, SIGGRAPH Asia), and for several international journals (e.g., T-PAMI, T-IP, CVIU, SPL, T-CSVT, MVA, PR, JVCIR, etc).

[Biography]

Selected Publications:

Note: Conferences are the major publication forum in the computer vision field. The top three computer vision conferences (ICCV, ECCV, CVPR) are highly competitive with low acceptance rates of around 25%. ICCV and ECCV have CiteSeer impact factor rankings in the top 5% and 7%, respectively, of all computer science journals and conferences. IEEE TPAMI is considered as one of the top two computer vision journals and has a very high journal impact factor that is ranked No.1 in all IEEE publication, No.1 in both electrical engineering and artificial intelligence, and among top 3 in all computer science journals.

Comments and suggestions for the improvement of the papers are highly welcome!

	Jialue Fan, Xiaohui Shen, and Ying Wu. Scribble Tracker: A Matting-based Approach for Robust Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2012. IEEE computer Society Digital Library. IEEE Computer Society, < http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.257 > [PDF (preprint), also available at PAMI preprint \| Project Page \| PPT \| Executable Code \| bibtex] We achieve the target boundary, instead of the rectangular bounding box. The proposed method alleviates drift, and it naturally handles scale change, out of plane rotation, fast motion, large deformation, and severe occlusion. The automatic generated scribble trimap is very informative in tracking, and it provides the rough location of the target. So this scribble trimap can be a complementary tool for other video tracking methods. The conference version has been published in ECCV 2010. For the executable code, my plan is to release it when the paper is formally published.
	Jialue Fan, Ying Wu, and Shengyang Dai. Discriminative Spatial Attention for Robust Tracking. European Conference on Computer Vision (ECCV) 2010. [PDF \| Extended TR \| Project Page \| PPT \| Executable Code \| bibtex] We study spatial distraction, which is one of the major reasons leading to tracking failure. We define the concept of discriminative mragin to measure the region discrimination, and design an efficient method to select discriminative reigions for object tracking. (acceptance rate: overall 27.6%, “motion and tracking” area 22.7%)
	Jialue Fan, Xiaohui Shen, and Ying Wu. Closed-Loop Adaptation for Robust Tracking. European Conference on Computer Vision (ECCV) 2010. [PDF \| Project Page \| PPT \| bibtex] Joint tracking and matting for reliable model updating/model adaptation. (acceptance rate: overall 27.6%, “motion and tracking” area 22.7%)
	Jialue Fan, Wei Xu, Ying Wu, and Yihong Gong. Human Tracking Using Convolutional Neural Networks. IEEE Transactions on Neural Networks (TNN), vol.21, no.10, pp.1610-1623, Oct. 2010. [PDF \| bibtex]
	Ying Wu and Jialue Fan. Contextual Flow. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009 (Oral). [PDF \| Project Page \| PPT \| bibtex] We leap from brightness constancy to context constancy, and present a new approach that incorporates contexts to constrain motion estimation for target tracking. (acceptance rate for oral presentation: overall 4.1%, “motion and tracking” area 5.7%)

Disclaimer: Electronic papers shared on the website are for timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders (corresponding publishers). All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Contact:

Email: jialue DOT fan AT northwestern DOT edu

last update: 3/3/2011

	Jialue Fan, Xiaohui Shen, and Ying Wu. Scribble Tracker: A Matting-based Approach for Robust Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2012. IEEE computer Society Digital Library. IEEE Computer Society, < http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.257 > [PDF (preprint), also available at PAMI preprint \| Project Page \| PPT \| Executable Code \| bibtex] We achieve the target boundary, instead of the rectangular bounding box. The proposed method alleviates drift, and it naturally handles scale change, out of plane rotation, fast motion, large deformation, and severe occlusion. The automatic generated scribble trimap is very informative in tracking, and it provides the rough location of the target. So this scribble trimap can be a complementary tool for other video tracking methods. The conference version has been published in ECCV 2010. For the executable code, my plan is to release it when the paper is formally published.
	Jialue Fan, Ying Wu, and Shengyang Dai. Discriminative Spatial Attention for Robust Tracking. European Conference on Computer Vision (ECCV) 2010. [PDF \| Extended TR \| Project Page \| PPT \| Executable Code \| bibtex] We study spatial distraction, which is one of the major reasons leading to tracking failure. We define the concept of discriminative mragin to measure the region discrimination, and design an efficient method to select discriminative reigions for object tracking. (acceptance rate: overall 27.6%, “motion and tracking” area 22.7%)
	Jialue Fan, Xiaohui Shen, and Ying Wu. Closed-Loop Adaptation for Robust Tracking. European Conference on Computer Vision (ECCV) 2010. [PDF \| Project Page \| PPT \| bibtex] Joint tracking and matting for reliable model updating/model adaptation. (acceptance rate: overall 27.6%, “motion and tracking” area 22.7%)
	Jialue Fan, Wei Xu, Ying Wu, and Yihong Gong. Human Tracking Using Convolutional Neural Networks. IEEE Transactions on Neural Networks (TNN), vol.21, no.10, pp.1610-1623, Oct. 2010. [PDF \| bibtex]
	Ying Wu and Jialue Fan. Contextual Flow. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009 (Oral). [PDF \| Project Page \| PPT \| bibtex] We leap from brightness constancy to context constancy, and present a new approach that incorporates contexts to constrain motion estimation for target tracking. (acceptance rate for oral presentation: overall 4.1%, “motion and tracking” area 5.7%)