Ce Liu

I recently moved from Microsoft Research New England to Google @ Cambridge!

Research Scientist

Google

Research Affiliate

Computer Science and Artificial Intelligence Laboratory (CSAIL)

Massachusetts Institute of Technology

 

   
     

Address

Google

355 Main St, Cambridge, MA 02142

 

Email:

Homepage:  (Google, coming soon!)
  http:/people.csail.mit.edu/celiu/ (MIT)

Curriculum vitae [pdf] or http://people.csail.mit.edu/celiu/CV.html

Education and Working Experience

  • 2014~now, Research Scientist at Google Research @ Cambridge.
  • 2009~now, Research Affiliate at CSAIL MIT
  • 2010~2014, Researcher at Microsoft Research New England.
  • 2009~2010, Postdoct at Microsoft Research New England.
  • 2009, PhD, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology.
  • 2008, summer intern at Adobe Advanced Technology Labs.
  • 2005, summer intern at Interactive Visual Media Group, Microsoft Research.
  • 2002~2003, Assistant Researcher, Microsoft Research Asia.
  • 2002, Master of Engineering, Institute of Pattern Recognition and Intelligent Systems, Department of Automation, Tsinghua University.
  • 1999, Bachelor of Engineering, Department of Automation, Tsinghua University.

Publications

[1]

C. Liu and D. Sun. On Bayesian Adaptive Video Super Resolution. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014. [pdf]

[2]

L. Sharan, C. Liu, R. Rosenholtz and E. Adelson. Recognizing Materials Using Perceptually Inspired Features. International Journal of Computer Vision (IJCV), pp. 348-371, Vol. 103, Issue 3, July 2013. [pdf]

[3]

X.-J. Wang, L. Zhang, and C. Liu. Duplicate Discovery on 2 Billion Internet Images. In Proceedings of Big Data Workshop, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013. [pdf]

[4]

M. Rubinstein, A. Joulin, J. Kopf and C. Liu. Unsupervised Joint Object Discovery and Segmentation in Internet Images. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013. [pdf] [webpage]

[5]

J. Kim, C. Liu, F. Sha and K. Grauman. Deformable Spatial Pyramid Matching for Fast Dense Correspondences. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013. [pdf]

[6]

B. Liu, F. Sadeghi, M. Tappen, O. Shamir and C. Liu. Probabilistic Label Trees for Efficient Large Scale Image Classification. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013. [pdf]

[7]

X.-J. Wang, Z. Xu, L. Zhang, C. Liu and Y. Rui. Towards Indexing Representative Images on the Web. ACM International Conference on Multimedia (ACM MM), 2012. [pdf]

[8]

M. Rubinstein, C. Liu and W.T. Freeman. Annotation Propagation: Automatic Annotation of Large Image Databases via Dense Image Correspondence. European Conference on Computer Vision (ECCV), 2012. [pdf] Supplemental materials [coming soon!]

[9]

K. Karsch, C. Liu and S.B. Kang. Depth Extraction from Video Using Non-parametric Sampling. European Conference on Computer Vision (ECCV), 2012. Oral presentation. [pdf]

[10]

M. Tappen and C. Liu. A Bayesian Approach to Alignment-based Image Hallucination. European Conference on Computer Vision (ECCV), 2012. [pdf]

[11]

D. Sun and C. Liu. Non-causal Temporal Prior for Video Deblocking. European Conference on Computer Vision (ECCV), 2012. [pdf]

[12]

M. Rubinstein, C. Liu and W.T. Freeman. Towards Longer Long-Range Motion Trajectories. British Machine Vision Conference (BMVC), 2012. [pdf]

[13]

J. Yuen, C. L. Zitnick, C. Liu, and A. Torralba. A framework for encoding object-level image priors. Microsoft Research Technical Report, MSR-TR-2011-99, 2011. [pdf]

[14]

O. Tamuz, C. Liu, S. Belongie, O. Shamir and A. Kalai. Adaptively Learning the Crowd Kernel. 28th International Conference on Machine Learning (ICML), 2011. [pdf] Oral presentation.

[15]

C. Liu and D. Sun. A Bayesian Approach to Adaptive Video Super Resolution. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2011. [pdf] Oral presentation.

[16]

M. Rubinstein, C. Liu, P. Sand, F. Durand, W.T. Freeman. Motion Denoising with Application to Time-lapse Photography. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2011. [pdf]

[17]

C. Liu, J. Yuen and A. Torralba. Nonparametric Scene Parsing via Label Transfer. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 33, No. 12, 2011. [pdf] [webpage] [code & data]

[18]

C. Liu, J. Yuen and A. Torralba. SIFT flow: dense correspondence across different scenes and its application. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 33, No. 5, 2011. [pdf] [webpage]

[19]

W. T. Freeman and C. Liu. Markov Random Fields for Super-resolution and Texture Synthesis. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing, Chapter 10. MIT Press, 2011. [pdf] [webpage]

[20]

C. Liu, J. Yuen and A. Torralba and W. T. Freeman. SIFT flow: dense correspondence across different scenes and its application. In A. Blake, P. Kohli, and C. Rother, eds., Advances in Markov Random Fields for Vision and Image Processing. MIT Press, 2011. [webpage]

[21]

C. Liu and W. T. Freeman. A High-Quality Video Denoising Algorithm based on Reliable Motion Estimation. European Conference on Computer Vision (ECCV) 2010. [pdf] [webpage] Oral presentation.

[22]

C. Liu, L. Sharan, E. H. Adelson and R. Rosenholtz. Exploring features in a Bayesian framework for material recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010. [pdf] [webpage]

[23]

J. Yuen, B. Russell, C. Liu, and A. Torralba. LabelMe video: Building a Video Database with Human Annotations. IEEE Intertional Conference on Computer Vision (ICCV), Oct 2009. [pdf]

[24]

C. Liu. Beyond pixels: exploring new representations and applications for motion analysis. Doctoral Thesis. Massachusetts Institute of Technology. 2009. [pdf]

[25]

C. Liu, J. Yuen, and A. Torralba.Nonparametric scene parsing: label transfer via dense scene alignment. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2009. Oral presentation. [pdf] Oral presentation. Best Student Paper Award.

[26]

C. Liu, J. Yuen, A. Torralba, J. Sivic, and W. T. Freeman. SIFT flow: dense correspondence across different scenes. European Conference on Computer Vision (ECCV) 2008. Oral presentation. [pdf] Oral presentation.

[27]

C. Liu, W. T. Freeman, E. H. Adelson and Y. Weiss. Human-assisted motion annotationIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. [pdf] [webpage]. Oral presentation.

[28]

C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick and W. T. Freeman. Automatic estimation and removal of noise from a single image. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 30, No. 2, Feb. 2008. [pdf] [MSR TR link]

[29]

B. Russell, A. Torralba, C. Liu, R. Fergus and W. T. Freeman. Object recognition by scene alignment. Advances in Neural Information Processing Systems (NIPS), 2007. [pdf] [webpage]

[30]

C. Liu, H. Y. Shum and W. T. Freeman. Face hallucination: theory and practice. International Journal of Computer Vision (IJCV), Vol. 75, No. 1, pp. 115-134, October, 2007. [pdf] [webpage] [SpringerLink]

[31]

M. F. Tappen, C. Liu, E. H. Adelson and W. T. Freeman. Learning Gaussian conditional random fields for low-level vision. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1-8, 2007. [pdf]

[32]

C. Liu, W. T. Freeman and E. H. Adelson. Analysis of contour motions. Advances in Neural Information Processing Systems (NIPS) 2006, oral presentation. [pdf] [ppt] [webpage] Oral presentation. Outstanding Student Paper Award.

[33]

C. Liu, W. T. Freeman, R. Szeliski and S. B. Kang. Noise estimation from a single image. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 901-908, 2006. [pdf] [ppt] [webpage] Oral presentation.

[34]

C. Liu, A. Torralba, W.T . Freeman, F. Durand and E. H. Adelson. Motion magnification. ACM SIGGRAPH 2005, pp. 519-526, 2005. [pdf] [ppt] [webpage] Oral presentation.

[35]

L. Yuan, F. Wen, C. Liu and H. Y. Shum. Synthesizing dynamic texture with closed-loop linear dynamic system. European Conference on Computer Vision (ECCV), 2004. [pdf] Oral presentation.

[36]

C. Y. Wu, C. Liu, H. Y. Shum, Y. Q. Xu and Z. Y. Zhang. Automatic eyeglasses removal from face images. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 26, No. 3, pp. 322-336, March 2004. [pdf]

[37]

C. Liu and H. Y. Shum. Kullback-Leibler boosting. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 587-594, 2003. [pdf] [ppt] Oral presentation.

[38]

S. C. Yan, C. Liu, S. Z. Li, H.J. Zhang, H. Shum, Q. S. Cheng. Face alignment using texture constrained active shape models. Image and Vision Computing, Vol. 21, Issue 1, Pages 69-75, January, 2003. [pdf]

[39]

Z. Q. Liu, C. Liu, H.Y . Shum and Y. Z. Yu. Pattern-based texture metamorphosis. Pacific Conference on Computer Graphics and Applications, pp. 184-193, 2002. [pdf] [ppt] [webpage] Oral presentation.

[40]

S.C. Yan, C. Liu, S. Z. Li, L. Zhu, Z, H.J. Zhang, H. Y. Shum and Q. S. Cheng. Texture constrained active shape models. ECCV 2002 Workshop on Generative Model Based Vision. Copenhagen , Denmark . May, 2002. [pdf]

[41]

C. Liu, H. Y. Shum and S.C. Zhang. Hierarchical shape model for automatic face localization. European Conference on Computer Vision (ECCV), pp. 687-703, 2002. [pdf]

[42]

C. Y. Wu, C. Liu, H. Y. Shum, Y. Q. Xu and Z. Y. Zhang. Automatic eyeglasses removal from face images. Asian Conference on Computer Vision (ACCV), pp. 193-198, 2002. [pdf] Oral presentation.

[43]

C. Liu, H. Y. Shum and C. S. Zhang. Two-step approach to hallucinating faces: global parametric model and local nonparametric model. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Vol. 1, pp. 192-198, 2001. [pdf] [ppt] [webpage] Oral presentation.

[44]

C. Y. Wu, C. Liu and J. Zhou. Eyeglasses verification by support vector machine. IEEE Pacific Ring Conference on Multimedia, pp. 1126-1131, 2001.

[45]

L. Liang, C. Liu, Y. Q. Xu, B. N. Guo and H. Y. Shum. Real-time texture synthesis by patch-based sampling. ACM Transactions on Graphics (TOG), Vol. 20, No. 3, pp. 127-150, July 2001. [pdf] [webpage]

[46]

C. Liu, S.C. Zhu and H. Y. Shum. Learning inhomogeneous Gibbs model of faces by minimax entropy. IEEE International Conference on Computer Vision (ICCV), pp. 281-287, 2001. [pdf] [webpage]

Referred Abstracts

[47]

C. Liu, E. H. Adelson and W. T. Freeman. Human-assisted motion annotation for real-world videos. Presented at Vision Science Society (VSS), Naples, Florida, May 2008.

[48]

L. Sharan, C. Liu, E. H. Adelson and R. Rosenholtz. A computational model for material recognition. Presented at Vision Science Society (VSS), Naples, Florida, May 2010.

Talks

Oct 2001

MSRA TAB Meeting

Face hallucination: global parametric and local nonparametric model

Feb 2002

U.C. Berkley

Face hallucination: global parametric and local nonparametric model

Aug 2005

SIGGRAPH

Motion magnification

Jun 2006

CVPR

Automatic noise estimation from a single image

Oct 2006

CSAIL MIT

Motion analysis: what can computers see and what can humans?

Dec 2006

NIPS

Analysis of contour motions

Mar 2008

CSAIL MIT

Bridging the gap between human and computer analysis on motion

May 2008

VSS

Human-assisted motion annotation for real-world videos

Jun 2008

CVPR

Human-assisted motion annotation

Aug 2008
Xerox How to make the computer see the moving world
Oct 2008
University of Cambridge SIFT flow: dense correspondence across scenes
Oct 2008
ECCV SIFT flow: dense correspondence across scenes
Oct 2008
CSAIL MIT Go beyond pixels--exploring new representations and applications for motion analysis
Dec 2008
SEAS Harvard Go beyond pixels--exploring new representations and applications for motion analysis
Jan 2009 SUnS workship Dense scene alignment
Mar 2009
MSR New England Beyond pixels--exploring new representations and applications for motion analysis
Jun 2009
CVPR Nonparametric scene parsing: label transfer via dense scene alignment
July 2009 UCSD SIFT flow: dense scene alignment and its applications
Oct, 2009 Brown University SIFT flow: dense scene alignment and its applications
Oct, 2009 Dartmouth College SIFT flow: dense scene alignment and its applications
Dec, 2009 Boston University Beyond pixels--exploring new representations and applications for motion analysis
Apr, 2010 New York University Exploring new models and features for visual recognition
Apr, 2010 MIT Guest lecture on computer vision
Apr, 2011 MIT Guest lecture on computervision
Jun 2011 CVPR A Bayesian approach to adaptive video super resolution
Aug 2011 Computer Vision Frontier Froundation & core in computer vision: a system perspective
Oct 2011 U.T. Austin Sparisty via dense correspondences for videos and large-scale image databases
Oct 2011 U.C. Florida Sparisty via dense correspondences for videos and large-scale image databases
Oct 2011 Adobe Research Exploring temporal sparisty for video enhancement

 

Last update: Aug, 2012