PUBLICATIONS

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Google Scholar Citations

Computer vision

  • Shape Recipes: Scene Representations that Refer to the Image
    William T. Freeman, Antonio Torralba
    Neural Information Processing Systems (NIPS) 2002
    Paper (pdf)
  • A World of Movement
    Fredo Durand, William T. Freeman, Michael Rubinstein
    Scientific American, Volume 312, Number 1, January 2015
    Paper (pdf)
    :
    videos
  • Estimating the Material Properties of Fabric from Video
    Katherine L. Bouman, Bei Xiao, Peter Battaglia, William T. Freeman
    2013 IEEE International Conference on Computer Vision (ICCV)
    Paper (pdf)
    :
    Project page
  • Group Norm for Learning Structured SVMs with Unstructured Latent Variables
    Daowen Chen, Dhruv Batra, William T. Freeman
    2013 IEEE International Conference on Computer Vision (ICCV)
    Paper (pdf)
  • Shape Anchors for Data-Driven Multi-view Reconstruction
    Andrew Owens, Jianxiong Xiao, Antonio Torralba, William Freeman
    International Conference on Computer Vision (ICCV), 2013
    Paper (pdf)
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    Project page
  • Structural modal identification through high speed camera video
    Justin G Chen, Neal Wadhwa, Young-Jin Cha, Frédo Durand, William T. Freeman, Oral Buyukozturk
    Topics in Modal Analysis I, Volume 7, pages 191-197, Springer International Publishing, 2014.
    Paper (pdf)
  • The Visual Microphone: Passive Recovery of Sound from Video
    Abe Davis, Michael Rubinstein, Neal Wadhwa, Gautham Mysore, Fredo Durand, William T. Freeman
    ACM Transactions on Graphics, Volume 33, Number 4 (Proc. SIGGRAPH), 2014.
    Paper (pdf)
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    Project web page
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    Wait, Wait Don’t Tell Me segment (starts at minute 3:28)
    :
    Chinese television (CCTV)
  • Refraction Wiggles for Measuring Fluid Depth and Velocity from Video
    Tianfan Xue, Michael Rubinstein , Neal Wadhwa , Anat Levin, Frédo Durand, William T. Freeman
    European Conference on Computer Vision (ECCV), 2014
    Paper (pdf)
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    Project page
  • Riesz Pyramids for Fast Phase-Based Video Magnification
    Neal Wadhwa, Michael Rubinstein, Frédo Durand, William T. Freeman
    International Conference on Computational Photography (ICCP), 2014.
    Paper (pdf)
    :
    Project page
  • Seeing the Arrow of Time
    Lyndsey Pickup, Zheng Pan, Donglai Wei, Yichang Shih, Andrew Zisserman, William T. Freeman, Bernhard Schoelkopf
    IEEE Computer Vision and Pattern Recognition (CVPR), 2014
    Paper (pdf)
    :
    Project page (and data)
  • A Compositional Model for Low-Dimensional Image Set Representation
    Hossein Mobahi, Ce Liu, and William T. Freeman
    IEEE Computer Vision and Pattern Recognition (CVPR), 2014
    Paper (pdf)
  • Camouflaging an Object from Many Viewpoints
    Andrew Owens, Connelly Barnes, Alex Flint, Hanumant Singh, William T. Freeman
    IEEE Computer Vision and Pattern Recognition (CVPR), 2014
    Paper (pdf)
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    Project page
  • Computer Image Processing of STEM Images of Tobacco Mosaic Virus
    E. J. Kirkland, W. T. Freeman, M. Ohtsuki, M. S. Isaacson, and B. S. Siegal
    Ultramicroscopy 6, 367-76 (1981)
  • Image processing to remove grain from photographs
    W. T. Freeman
    Society of Photographic Scientists and Engineers 42nd Annual Conference, pp. 457 – 460, May, 1989
  • Steerable filters
    W. T. Freeman and E. H. Adelson
    OSA Topical Meeting on Image Understanding and Machine Vision, Technical Digest Series Volume 14, June, 1989
  • Applications of neural networks in image processing
    W. T. Freeman, J. G. Chen, and Q. Tian
    Automation Soc. of China Symp. on Neural Networks, pp. 46 – 55, Beijing, 1989

    (in Chinese)

  • A neural network for image noise removal
    J. G. Chen, Q. Tian, and W. T. Freeman
    1st National Conference on Neural Networks and their Applications, Beijing, 1990

    (in Chinese)

  • Pyramids and multiscale representations
    E. H. Adelson, E. P. Simoncelli, and W. T. Freeman
    Proc. 13th European Conference on Visual Perception, Paris, 1990
    Paper (pdf)
  • Steerable filters for early vision, image analysis, and wavelet decomposition
    W. T. Freeman and E. H. Adelson
    IEEE International Conference on Computer Vision, Osaka, Japan, 1990

    Helmholtz Prize–test-of-time award winner.

  • Motion without movement
    W. T. Freeman, E. H. Adelson, and D. J. Heeger
    ACM Computer Graphics, vol. 25, no. 4, (SIGGRAPH ’91), pp. 27 – 30, July, 1991
  • The design and use of steerable filters
    W. T. Freeman and E. H. Adelson
    IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 13, no. 9, pp. 891 – 906, September, 1991
    Paper (pdf)
  • Shiftable Multi-Scale Transforms
    E. P. Simoncelli, W. T. Freeman, E. H. Adelson and D. J. Heeger
    IEEE Trans. Information Theory, Special Issue on Wavelets. Vol. 38, No. 2, pp. 587-607, March 1992
    Paper (pdf)
  • Steerable Filters and Local Analysis of Image Structure
    W. T. Freeman
    Ph.D. Thesis, Massachusetts Institute of Technology, 1992
    Paper (pdf)
  • Exploiting the generic view assumption to estimate scene parameters
    W. T. Freeman
    IEEE International Conference on Computer Vision, Berlin, Germany, 1993
  • Building and using catalogs of grey-level junctions
    E. H. Adelson, P. Sinha, and W. T. Freeman
    Proc. 15th European Conference on Visual Perception, Edinburgh, Scotland. August, 1993
  • Bayesian method for recovering surface and illuminant properties from photosensor responses
    D. H. Brainard and W. T. Freeman
    Human Vision, Visual Processing and Digital Display V, SPIE Proceedings Series, vol. 2179, 1994
  • The generic viewpoint assumption in a framework for visual perception
    W. T. Freeman
    Nature, vol. 368, p. 542 – 545, April 7, 1994
    Paper (pdf)
  • Computer vision for computer graphics
    I. Carlbom (course organizer) and W. Freeman, G. Klinker, W. Lorensen, R. Szeliski, D. Terzopoulos, and K. Waters
    SIGGRAPH ’94 and ’95 course notes
  • Demonstration of an interactive environment for collaboration and learning
    C. Rich, R. C. Waters, C. Strohecker, Y. Schabes, W. T. Freeman, M. C. Torrance, A. R. Golding, and M. Roth
    IEEE Computer, Vol. 27, No. 12, Dec. 1994
  • Orientation histograms for hand gesture recognition
    W. T. Freeman and M. Roth
    International Workshop on Automatic Face- and Gesture- Recognition, IEEE Computer Society, Zurich, Switzerland, June, 1995, pp. 296-301

    Winner, 2013 Test-of-time award from Face and Gesture Recognition conference. Here is a video prepared to accept the test-of-time award, describing the work in its context, in .mov format, or in .mpeg format.

    Paper (pdf)
  • Television control by hand gestures
    W. T. Freeman and C. Weissman
    International Workshop on Automatic Face- and Gesture- Recognition, IEEE Computer Society, Zurich, Switzerland, June, 1995, pp. 179-183
    Paper (pdf)
  • Bayesian decision theory, the maximum local mass estimate, and color constancy
    W. T. Freeman and D. H. Brainard
    Fifth International Conference on Computer Vision, IEEE Computer Society, Cambridge, MA, U.S.A, June, 1995, pp. 210 – 217
    Paper (pdf)
  • The steerable pyramid: a flexible architecture for multi-scale derivative computation
    E. P. Simoncelli and W. T. Freeman
    2nd Annual IEEE International Conference on Image Processing, Washington, DC. October, 1995
    Paper (pdf)
  • Artificial retina chips as image input interfaces for multimedia systems
    T. Toyoda, Y. Nitta, E. Funatsu, Y. Miyake, W. Freeman, J. Ohta, and K. Kyuma
    Optoelectronics and Communications Conference, OECC’96, Chiba, Japan, July, 1996
  • A gesture controlled human interface using an artificial retina chip
    Y. Miyake, W. T. Freeman, J. Ohta, K. Tanaka, and K. Kyuma
    IEEE Lasers and Electro-Optics (LEOS ’96), July, 1996
  • Example-based head tracking
    S. Niyogi and W. T. Freeman
    2nd International Conference on Automatic Face and Gesture Recognition, Killington, VT, USA.
    Paper (pdf)
  • Computer vision for computer games
    W. T. Freeman, K. Tanaka, J. Ohta, and K. Kyuma
    , 2nd International Conference on Automatic Face and Gesture Recognition, Killington, VT, USA, pp. 100-105
    Paper (pdf)
  • The generic viewpoint assumption in a Bayesian framework
    W. T. Freeman
    Perception as Bayesian Inference, D. Knill and W. Richards, eds., Cambridge University Press, 365 – 390, 1996
    Paper (pdf)
  • Exploiting the generic viewpoint assumption
    W. T. Freeman
    International Journal Computer Vision, 20 (3), 243-261, 1996
    Paper (pdf)
  • Separating Style and Content
    J. B. Tenenbaum and W. T. Freeman
    Neural Information Processing Systems 9, M. C. Mozer, M. I. Jordan and T. Petsche, Eds., Morgan Kaufmann, San Mateo, CA., 1997
    Paper (pdf)
  • Learning bilinear models for two-factor problems in vision
    W. T. Freeman and J. B. Tenenbaum
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’97), Puerto Rico, U. S. A., June, 1997

    Received Outstanding Paper prize, CVPR '97

    Paper (pdf)
  • Bayesian Color Constancy
    D. H. Brainard and W. T. Freeman
    Journal of the Optical Society of America, A, 14(7), pp. 1393-1411, July, 1997
    Paper (pdf)
  • Bayesian Estimation of 3-D Human Motion
    Michael E. Leventon, William T. Freeman
    Tech. Rep. TR98-06, Mitsubishi Electric Research Laboratories, Cambridge, MA, July 1998
    Paper (pdf)
  • Bayesian model of surface perception
    W. T. Freeman and P. A. Viola
    Neural Information Processing Systems, volume 10, pp. 787-793, 1998
    Paper (pdf)
  • Computer vision for interactive computer graphics
    W. T. Freeman, D. Anderson, P. Beardsley, C. Dodge, H. Kage, K. Kyuma, Y. Miyake, M. Roth, K. Tanaka, C. Weissman, W. Yerazunis
    IEEE Computer Graphics and Applications, volume 18, number 3, May-June, pp. 42-53, 1998
    Paper (pdf)
  • A factorization approach to grouping
    P. Perona and W. T. Freeman
    Proceedings, European Conference on Computer Vision, 1998
    Paper (pdf)
  • Separating style and content with bilinear models
    Joshua B. Tenenbaum, William T. Freeman
    Neural Computation 12(6), pp. 1247-1283, 2000
    Paper (pdf)
  • Learning to estimate scenes from images
    William T. Freeman, Egon C. Pasztor
    Neural Information Processing Systems, volume 11, 1999
    Paper (pdf)
  • Markov networks for low-level vision
    William T. Freeman, Egon C. Pasztor
    Presented at Workshop on Statistical and Computational Theories of Vision
    Paper (pdf)
  • Learning low-level vision
    William T. Freeman, Egon C. Pasztor
    Appeared in IEEE International Conference on Computer Vision, Corfu, Greece, 1999
    Paper (pdf)
  • An Inexpensive, All Solid-state Video and Data Recorder for Accident Reconstruction
    W. S. Yerazunis, D. L. Leigh, W. T. Freeman, R. S. Bardsley
    Presented at the 1999 SAE International Congress and Exposition in Detroit, Michigan on March 3, 1999; published as SAE Technical Paper number 1999-10-1299
    Paper (pdf)
  • Computer vision for computer interaction
    W. T. Freeman, P. Beardsley, H. Kage, K. Tanaka, K. Kyuma, C. Weissman
    SIGGRAPH Computer Graphics magazine, November, 1999
    Paper (pdf)
  • Bayesian Reconstruction of 3D Human Motion from Single-Camera Video
    Nicholas R. Howe, Michael E. Leventon, William T. Freeman
    Advances in Neural Information Processing Systems 12, edited by S. A. Solla, T. K. Leen, and K-R Muller, 2000
    Paper (pdf)
  • Artificial retina chips as on-chip image processors and gesture-oriented interfaces
    H. Kage, W. T. Freeman, Y. Miyake, E. Funatsu, K. Tanaka, K. Kyuma
    Optical Engineering, Vol. 38, No. 12, December, 1999
    Paper (pdf)
  • Learning Low-Level Vision
    W. T. Freeman, E. C. Pasztor, O. T. Carmichael
    International Journal of Computer Vision, 40(1), pp. 25-47, 2000
    Paper (pdf)
  • Markov networks for super-resolution
    W. T. Freeman and E. C. Pasztor
    Proceedings of 34th Annual Conference on Information Sciences and Systems (CISS 2000), Dept. Electrical Engineering, Princeton University, Princeton, NJ 08544-5263, March, 2000
    Paper (pdf)
  • Learning Motion Analysis
    W. T. Freeman, J. A. Haddon, and E. C. Pasztor
    Statistical Theories of the Brain, edited by R. Rao, B. Olshausen, and M. Lewicki, MIT Press, 2001
    Paper (pdf)
  • Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
    J. W. Fisher, T. Darrell, W. T. Freeman and P. Viola
    Advances in Neural Information Processing Systems 13, edited by T. K. Leen, T. G. dietterich, and V. Tresp, pp. 772-778, 2001
  • Example-based super-resolution
    William T. Freeman, Thouis R. Jones, and Egon C. Pasztor
    IEEE Computer Graphics and Applications, March/April, 2002.

     Test-of-time award given in 2023 from IEEE CG&A.

    Paper (pdf)
    :
    Project website
  • Learning local evidence for shading and reflectance
    M. Bell and W. T. Freeman
    International Conference on Computer Vision, Vancouver, BC, Canada, 2001
    Paper (pdf)
  • Shape-Time Photography
    W. T. Freeman and H. Zhang
    MIT Artificial Intelligence Lab Memo 2002-002
    Paper (pdf)
  • Learning style translation for the lines of a drawing
    W. T. Freeman, J. B. Tenenbaum, E. Pasztor
    ACM Transactions on Graphics, January, 2003
    Paper (pdf)
  • Properties and Applications of Shape Recipes
    A. Torralba and W. T. Freeman
    IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003
    Paper (pdf)
  • Nonparametric Belief Propagation and Facial Appearance Estimation
    E. B. Sudderth, A. T. Ihler, W. T. Freeman and A. S. Willsky
    IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003
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    Project website
  • Shape-Time Photography
    W. T Freeman and H. Zhang
    IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003
    Paper (pdf)
  • Context-based vision system for place and object recognition
    A. Torralba, K. P. Murphy, W. T. Freeman, and M. A. Rubin
    IEEE Intl. Conference on Computer Vision (ICCV), Nice, France, October, 2003
    Paper (pdf)
  • Comparison of graph cuts with belief propagation for stereo, using identical MRF parameters
    M. F. Tappen and W. T. Freeman
    IEEE Intl. Conference on Computer Vision (ICCV), Nice, France, October, 2003
    Paper (pdf)
  • Exploiting spatial and spectral image regularities for color constancy
    B. Singh, W. T. Freeman, and D. H. Brainard
    3rd Intl. Workshop on Statistical and Computational Theories of Vision (associated with Intl. Conf. on Computer Vision), Nice, France, October, 2003
    Paper (pdf)
  • Exploiting the sparse derivative prior for super-resolution and image demosaicing
    M. F. Tappen, B. C. Russell, and W. T. Freeman
    3rd Intl. Workshop on Statistical and Computational Theories of Vision (associated with Intl. Conf. on Computer Vision), Nice, France, October, 2003
    Paper (pdf)
  • Using the forest to see the trees: a graphical model relating features, objects, and scenes
    K. Murphy, A. Torralba, and W. T. Freeman
    Advances in Neural Information Processing Systems 16 (NIPS), Vancouver, BC, MIT Press, 2004
    Paper (pdf)
  • Visual Hand Tracking Using Nonparametric Belief Propagation
    E. Sudderth, M. Mandel, W. Freeman, and A. Willsky
    Workshop on Generative Model Based Vision, CVPR, June 2004
    :
    Project website
  • Efficient graphical models for processing images
    M. F. Tappen, B. C. Russell, and W. T. Freeman
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Washington, DC, 2004
    Paper (pdf)
  • Single-frame Text Super-resolution: A Bayesian Approach
    G. Dalley, W. T. Freeman, and J. Marks
    International Conference on Image Processing (ICIP), Oct. 2004
    Paper (pdf)
  • Sharing visual features for multiclass and multiview object detection
    A. Torralba, K. P. Murphy, and W. T. Freeman
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) Washington, DC, 2004; MIT CSAIL technical report
    Paper (pdf)
  • Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation
    Propagation E. Sudderth, M. Mandel, W. Freeman, and A. Willsky
    Neural Information Processing Systems (NIPS) 2004
    Paper (pdf)
  • Contextual Models for Object Detection Using Boosted Random Fields
    Antonio Torralba, Kevin P. Murphy, William T. Freeman
    Neural Information Processing Systems (NIPS), Vancouver, B.C., Dec. 2004
    Paper (pdf)
  • Motion Magnification
    Ce Liu, Antonio Torralba, William Freeman, Fredo Durand, and Edward Adelson
    SIGGRAPH 2005
    Paper (pdf)
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    Project website
  • Learning Hierarchical Models of Scenes, Objects, and Parts
    E. Sudderth, A. Torralba, W. Freeman, and A. Willsky
    International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005
    Paper (pdf)
  • An Ensemble Prior of Image Structure for Cross-modal Inference
    S. Ravela, A. Torralba, W. T. Freeman
    International Conference on Computer Vision (ICCV), Beijing, China, vol. 1, pp. 871-876, Oct. 2005
    Paper (pdf)
  • Discovering Objects and their Location in Images
    J. Sivic, B. Russell, A. A. Efros, A. Zisserman, W. T. Freeman
    International Conference on Computer Vision (ICCV), Beijing, China, Oct. 2005

    Received 2017 Helmholtz prize, test-of-time award.

    Paper (pdf)
  • Describing Visual Scenes using Transformed Dirichlet
    E. Sudderth, A. Torralba, W. Freeman, and A. Willsky
    Neural Information Processing Systems (NIPS), Vancouver, B.C., Dec. 2005
  • Using multiple segmentations to discover objects and their extent in image collections
    B. C. Russell, , A. Efros, J. Sivic, W. T. Freeman, and A. Zisserman
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006
  • Noise estimation from a single image
    C. Liu, W. T. Freeman, R. Szeliski, and S. B. Kang
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006
    Paper (pdf)
  • Depth from familiar objects: a hierarchical model for 3d scenes
    E. Sudderth, A. Torralba, W. T. Freeman, and A. Willsky
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006
    Paper (pdf)
  • Removing camera shake from a single image
    R. Fergus, B. Singh, A. Hertzmann, S. Roweis, and W. T. Freeman
    SIGGRAPH 2006
    Paper (pdf)
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    Project website
  • LabelMe: a database and web-based tool for image annotation
    B. Russell, A. Torralba, K. Murphy, W. T. Freeman
    MIT AI Lab Memo AIM-2005-025, September, 2005
    Paper (pdf)
  • Shared features for multiclass object detection
    A. Torralba, K. Murphy, W. T. Freeman
    Towards Category-Level Object Recognition. Springer Lecture Notes in Computer Science (invited submission). 2005
    Paper (pdf)
  • Recovering Intrinsic Images from a Single Image
    M. F. Tappen, W. T. Freeman, and E. H. Adelson
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 27, Issue 9, September 2005, Pages 1459 – 1472
    Paper (pdf)
  • Object detection and localization using local and global features
    K. Murphy, A. Torralba, D. Eaton, W. T. Freeman
    Lecture Notes in Computer Science (unrefeered). Sicily workshop on object recognition, 2005
    Paper (pdf)
  • Bayesian model of human color constancy
    D. H. Brainard, P. Longere, P. B. Delahunt, W. T. Freeman, J. M. Kraft, and B. Xiao
    Journal of Vision, 6, 1267-1281, doi:10.1167/6.11.10. 2006

    http://journalofvision.org/6/11/10/

    Paper (pdf)
  • Analysis of contour motions
    C. Liu, W. T. Freeman and E. H. Adelson
    Advances in Neural Information Processing Systems (NIPS 2006)

    Received Outstanding Student Paper Award

    Paper (pdf)
  • Sharing visual features for multiclass and multiview object detection
    A. Torralba, K. P. Murphy, and W. T. Freeman
    IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 29, no. 5, pp. 854-869, May, 2007
    Paper (pdf)
  • Image and depth from a conventional camera with a coded aperture
    A. Levin, R. Fergus, F. Durand, and W. T. Freeman
    ACM Trans. On Graphics (Proc. SIGGRAPH) 2007
    Paper (pdf)
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    Project website
  • Face Hallucination: theory and practice
    C. Liu, H. Y. Shum and W. T. Freeman
    International Journal of Computer Vision, Vol. 75, no. 1, pp. 115-134, October, 2007
    Paper (pdf)
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    Project website
  • What makes a good model of natural images?
    Y. Weiss and W. T. Freeman
    IEEE Computer Vision and Pattern Recognition (CVPR) 2007
    Paper (pdf)
  • Exploring defocus matting: non-parametric acceleration, super-resolution, and off-center matting
    N. Joshi, W. Matusik, S. Avidan, H. Pfister, and W. T. Freeman
    IEEE Computer Graphics and Applications, special issue on Computational Photography, March, 2007
    Paper (pdf)
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    Project website
  • A reliable skin mole localization scheme
    Taeg Sang Cho, William T. Freeman, Hensin Tsao
    2007 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), in conjunction with 2007 ICCV
    Paper (pdf)
  • Estimating Intrinsic Component Images using Non-Linear Regression
    M. Tappen, E. Adelson, and W. T. Freeman
    IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) New York, NY, June, 2006
    Paper (pdf)
  • Learning Gaussian Conditional Random Fields for Low-Level Vision
    M. F. Tappen, C. Liu, W. T. Freeman, and E. H. Adelson
    IEEE Computer Vision and Pattern Recognition (CVPR) 2007
    Paper (pdf)
  • Signal and Image Processing with Belief Propagation
    E. Sudderth and W. T. Freeman
    DSP Application Column, IEEE Signal Processing Magazine, Mar. 2008
    Paper (pdf)