Publication statistics

Pub. period:2003-2012
Pub. count:10
Number of co-authors:29



Co-authors

Number of publications with 3 favourite co-authors:

Mingjing Li:
Wei-Ying Ma:
Zhiwei Li:

 

 

Productive colleagues

Jue Wang's 3 most productive colleagues in number of publications:

Wei-Ying Ma:95
Michael F. Cohen:27
Mingjing Li:20
 
 
 

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Jue Wang

 

Publications by Jue Wang (bibliography)

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2012
 
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Yang, Fei, Shechtman, Eli, Wang, Jue, Bourdev, Lubomir and Metaxas, Dimitris (2012): Face morphing using 3D-aware appearance optimization. In: Proceedings of the 2012 Conference on Graphics Interface 2012. pp. 93-99. Available online

Traditional automatic face morphing techniques tend to generate blurry intermediate frames when the two input faces differ significantly. We propose a new face morphing approach that deals explicitly with large pose and expression variations. We recover the 3D face geometry of the input images using a projection on a pre-learned 3D face subspace. The geometry is interpolated by factoring the expression and pose and varying them smoothly across the sequence. Finally we pose the morphing problem as an iterative optimization with an objective that combines similarity of each frame to the geometry-induced warped sources, with a similarity between neighboring frames for temporal coherence. Experimental results show that our method can generate higher quality face morphing results for more extreme pose, expression and appearance changes than previous methods.

© All rights reserved Yang et al. and/or their publisher

2011
 
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Pongnumkul, Suporn, Dontcheva, Mira, Li, Wilmot, Wang, Jue, Bourdev, Lubomir, Avidan, Shai and Cohen, Michael F. (2011): Pause-and-play: automatically linking screencast video tutorials with applications. In: Proceedings of the 2011 ACM Symposium on User Interface Software and Technology 2011. pp. 135-144. Available online

Video tutorials provide a convenient means for novices to learn new software applications. Unfortunately, staying in sync with a video while trying to use the target application at the same time requires users to repeatedly switch from the application to the video to pause or scrub backwards to replay missed steps. We present Pause-and-Play, a system that helps users work along with existing video tutorials. Pause-and-Play detects important events in the video and links them with corresponding events in the target application as the user tries to replicate the depicted procedure. This linking allows our system to automatically pause and play the video to stay in sync with the user. Pause-and-Play also supports convenient video navigation controls that are accessible from within the target application and allow the user to easily replay portions of the video without switching focus out of the application. Finally, since our system uses computer vision to detect events in existing videos and leverages application scripting APIs to obtain real time usage traces, our approach is largely independent of the specific target application and does not require access or modifications to application source code. We have implemented Pause-and-Play for two target applications, Google SketchUp and Adobe Photoshop, and we report on a user study that shows our system improves the user experience of working with video tutorials.

© All rights reserved Pongnumkul et al. and/or ACM Press

2010
 
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Pongnumkul, Suporn, Wang, Jue, Ramos, Gonzalo and Cohen, Michael (2010): Content-aware dynamic timeline for video browsing. In: Proceedings of the 2010 ACM Symposium on User Interface Software and Technology 2010. pp. 139-142. Available online

When browsing a long video using a traditional timeline slider control, its effectiveness and precision degrade as a video's length grows. When browsing videos with more frames than pixels in the slider, aside from some frames being inaccessible, scrolling actions cause sudden jumps in a video's continuity as well as video frames to flash by too fast for one to assess the content. We propose a content-aware dynamic timeline control that is designed to overcome these limitations. Our timeline control decouples video speed and playback speed, and leverages video content analysis to allow salient shots to be presented at an intelligible speed. Our control also takes advantage of previous work on elastic sliders, which allows us to produce an accurate navigation control.

© All rights reserved Pongnumkul et al. and/or their publisher

2009
 
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Sun, Zhengya, Qin, Tao, Tao, Qing and Wang, Jue (2009): Robust sparse rank learning for non-smooth ranking measures. In: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2009. pp. 259-266. Available online

Recently increasing attention has been focused on directly optimizing ranking measures and inducing sparsity in learning models. However, few attempts have been made to relate them together in approaching the problem of learning to rank. In this paper, we consider the sparse algorithms to directly optimize the Normalized Discounted Cumulative Gain (NDCG) which is a widely-used ranking measure. We begin by establishing a reduction framework under which we reduce ranking, as measured by NDCG, to the importance weighted pairwise classification. Furthermore, we provide a sound theoretical guarantee for this reduction, bounding the realized NDCG regret in terms of a properly weighted pairwise classification regret, which implies that good performance can be robustly transferred from pairwise classification to ranking. Based on the converted pairwise loss function, it is conceivable to take into account sparsity in ranking models and to come up with a gradient possessing certain performance guarantee. For the sake of achieving sparsity, a novel algorithm named RSRank has also been devised, which performs L1 regularization using truncated gradient descent. Finally, experimental results on benchmark collection confirm the significant advantage of RSRank in comparison with several baseline methods.

© All rights reserved Sun et al. and/or their publisher

2008
 
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Pongnumkul, Suporn, Wang, Jue and Cohen, Michael F. (2008): Creating map-based storyboards for browsing tour videos. In: Cousins, Steve B. and Beaudouin-Lafon, Michel (eds.) Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology October 19-22, 2008, Monterey, CA, USA. pp. 13-22. Available online

2007
 
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Zhang, Guang-Jun, Wang, Jue, Xu, Jian-Xue, Wang, Xiang-Bo and Yao, Hong (2007): Mechanism of Bifurcation-Dependent Coherence Resonance of Excitable Neuron Model. In: Duffy, Vincent G. (ed.) ICDHM 2007 - First International Conference on Digital Human Modeling July 22-27, 2007, Beijing, China. pp. 757-766. Available online

 
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Wang, Jue, Yan, Nan, Liu, Hailong, Liu, Mingyu and Tai, Changfeng (2007): Brain-Computer Interfaces Based on Attention and Complex Mental Tasks. In: Duffy, Vincent G. (ed.) ICDHM 2007 - First International Conference on Digital Human Modeling July 22-27, 2007, Beijing, China. pp. 467-473. Available online

2006
 
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Yao, Jinyi, Wang, Jue, Li, Zhiwei, Li, Mingjing and Ma, Wei-Ying (2006): Ranking Web News Via Homepage Visual Layout and Cross-Site Voting. In: Lalmas, Mounia, MacFarlane, Andy, Rger, Stefan M., Tombros, Anastasios, Tsikrika, Theodora and Yavlinsky, Alexei (eds.) Advances in Information Retrieval - 28th European Conference on IR Research - ECIR 2006 April 10-12, 2006, London, UK. pp. 131-142. Available online

2003
 
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Di, Kaichang, Ma, Ruijin, Wang, Jue and Li, Ron (2003): Coastal Mapping and Change Detection Using High--Resolution IKONOS Satellite Imagery. In: DG.O 2003 2003. . Available online

 
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Di, Kaichang, Ma, Ruijin, Wang, Jue and Li, Ron (2003): Coastal Mapping and Change Detection Using High--Resolution IKONOS Satellite Imagery. In: DG.O 2003 2003. . Available online

 
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