Frédo Durand, William T. Freeman, Edward H. Adelson, Antonio Torralba


The digital photography revolution has greatly facilitated the way in which we take and share pictures. However, it has mostly relied on a rigid imaging model inherited from traditional photography. Computational photography and video go one step further and exploit digital technology to enable arbitrary computation between the light array and the final image or video. Such computation can overcome limitations of the imaging hardware and enable new applications. It can also enable new imaging setups and postprocessing tools that empower users to enhance and interact with their images and videos.

Contact; web:; web; web; web:
tel: (1) 617 253 6583 ; fax: (1) 617 253 4640


Conference and journal

IEEE CG&A special issue on Computational Photography

guest editors: Richard Szeliski and Frédo Durand
March/April 2007 (Vol. 27, No. 2)

Symposium on Computational Photography

May 2005, MIT
Slides available


Computational optics and defocus

Image and Depth from a Conventional Camera with a Coded Aperture
Anat Levin, Rob Fregus, Frédo Durand, William Freeman
ACM Transactions on Graphics, 26(3), (Proc.Siggraph), July 2007

Multi-aperture Photography
Paul Green, Wenyang Sun, Wojciech Matusik, Frédo Durand.
ACM Transactions on Graphics, 26(3), (Proc.Siggraph), July 2007

Defocus Magnification
Soonmin Bae and Frédo Durand
Proceedings of Eurographics 2007

Defocus Video Matting
Morgan McGuire, Wojciech Matusik, Hanspeter Pfister, John F. Hughes, and Frédo Durand

Plenoptic and light field imaging

Antialiasing for Automultiscopic Displays
M. Zwicker, W. Matusik, F. Durand, H. Pfister
Proceedings of Eurographics Symposium on Rendering, 2006.

A Frequency analysis of Light Transport
Frédo Durand, Nicolas Holzschuch, Cyril Soler, Eric Chan & François Sillion

Single Lens Stereo with a Plenoptic Camera
Adelson, E. H., and Wang J. Y. A.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2): 99-106 (1992).

The Plenoptic Function and the Elements of Early Vision
Adelson, E. H., and Bergen, J. R.
In M. Landy and J. A. Movshon (eds), Computational Models of Visual Processing, Cambridge, MA: MIT Press (1991).

Computational illumination

Flash Photography Enhancement Via Intrinsic Relighting
Elmar Eisemann and Frédo Durand

Image-based modeling & editing (3D from photo)

Image-Based Modeling and Photo Editing
Byong Mok Oh, Max Chen, Julie Dorsey and Frédo Durand
in the Proceedings of Siggraph'2001.

High-dynamic-range imaging & tone mapping

Real-time Edge-Aware Image Processing with the Bilateral Grid
Jiawen Chen, Sylvain Paris, Frédo Durand
ACM Transactions on Graphics, 26(3), (Proc.Siggraph), July 2007

Two-scale Tone Management for Photographic Look.
Soonmin Bae, Sylvain Paris, and Frédo Durand.
ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH'06)

A Fast Approximation of the Bilateral Filter using a Signal Processing Approach
Sylvain Paris and Frédo Durand
European Conference on Computer Vision (ECCV'06)
(Code provided!!)

Compressing and Companding High Dynamic Range Images with Subband Architectures.
Li, Y., Sharan, L., and Adelson, E. H.
ACM Transactions on Graphics (Siggraph Proceedings), 24(3): 836-844 (2005) .

Fast Bilateral Filtering for the Display of High-Dynamic-Range Images
Frédo Durand and Julie Dorsey

Matting and layer extraction

Exploring Defocus Matting: Nonparametric Acceleration, Super-Resolution, and Off-Center Matting
Neel Joshi, Wojciech Matusik Shai Avidan, Hanspeter Pfister, William T. Freeman
IEEE CG&A March/April 2007 (Vol. 27, No. 2)

Spectral Matting.
Anat Levin, Alex Rav-Acha, Dani Lischinski.
IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Minneapolis, June 2007
Separating Reflections from Images by Use of Independent Components Analysis,
H. Farid and E.H. Adelson,
Journal of the Optical Society of America A, 16(9):2136-2145, (1999)

Motion depiction

Motion Magnification
Ce Liu, Antonio Torralba, William T. Freeman, Frédo Durand and Edward H. Adelson

Shapetime photography
W. T Freeman and H. Zhang
IEEE Computer Vision and Pattern Recognition (CVPR), Madison, WI, June, 2003
Motion Without Movement
Freeman, W. T., Adelson, E. H., and Heeger, D. J.
ACM Computer Graphics (SIGGRAPH), 25(4):27-30 (1991).

Video analysis and representation

A Topological Approach to Hierarchical Segmentation using Mean Shift
Sylvain Paris and Frédo Durand
Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (CVPR'07)

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

Learning Motion Analysis
W. T. Freeman, J. A. Haddon, and E. C. Pasztor
To appear in "Statistical Theories of the Brain", edited by R. Rao, B. Olshausen, and M. Lewicki, MIT Press, 2001. MERL-TR2000-32.

Layered Representations for Vision and Video
Adelson, E. H.,
Proceedings of IEEE Workshop on Representation of Visual Scenes, in conjunction with ICCV '95, pp.3-9, Cambridge, MA; June (1995).

Applying Mid-Level Vision Techniques for Video Data Compression and Manipulation
Wang, J. Y. A., Adelson, E. H., and Desai, U.,
Proceedings of SPIE on Digital Video Compression on Personal Computers: Algorithms and Technologies, 2187:116-127 San Jose; February (1994).

Representing Moving Images with Layers
Wang, J. Y. A., and Adelson, E. H.
IEEE Transactions on Image Processing, 3(5):625-638, (1994).
Probability Distributions of Optical Flow
Simoncelli, E. P., Adelson, E. H., and Heeger, D. J.
IEEE Conference on Computer Vision and Pattern Recognition, Mauii, Hawaii; June (1991).

Deblurring, shake removal

Removing camera shake from a single image
R. Fergus, B. Singh, A. Hertzmann, S. Roweis, and W. T. Freeman

Texture synthesis and transfer

Image quilting for texture synthesis and transfer
A. Efros and W. T Freeman


Single-frame Text Super-resolution: A Bayesian Approach
G. Dalley, W. T. Freeman, and J. Marks
International Conference on Image Processing (ICIP), Oct. 2004

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

Example-based super-resolution
William T. Freeman, Thouis R. Jones, and Egon C. Pasztor
IEEE Computer Graphics and Applications, March/April, 2002.

Learning low-level vision.
William T. Freeman, Egon C. Pasztor
IEEE International Conference on Computer Vision, Corfu, Greece, 1999.

Learning to estimate scenes from images.
William T. Freeman, Egon C. Pasztor
Neural Information Processing Systems, volume 11, 1999


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

Noise Removal via Bayesian Wavelet Coring
Simoncelli, E. P., and Adelson, E. H.
Third IEEE International Conference on Image Processing. Lausanne, Switzerland; September (1996).
Subband Coring for Image Noise Reduction
Adelson, E. H.
Internal Report: RCA Sarnoff Labortories, Princeton, NJ (1986).

Image processing foundations

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.

Shiftable Multiscale Transforms
Simoncelli, E. P., Freeman, W. T., Adelson, E. H., and Heeger, D. J.
IEEE Transactions on Information Theory, 38:587-607 (1992).

Steerable Filters and Local Analysis of Image Structure
W. T. Freeman
Ph.D. Thesis, Massachusetts Institute of Technology, 1992

The Design and Use of Steerable Filters
Freeman, W. H., and Adelson, E. H.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 13:891-906 (1991).

Subband Transforms
Simoncelli, E., and Adelson, E. H.
In J. Woods (ed.), Subband Image Coding (pp. 143-192), Norwell, MA: Kluwer Academic Publishers (1991).

Orthogonal Pyramid Transforms for Image Coding
Adelson, E. H., Simoncelli, E., and Hingorani, R.
Visual Communications and Image Processing II, Proc. SPIE, Vol. 845, pp. 50-58 Cambridge, MA; October 27-29 (1987).

Pyramid-Based Computer Graphics
Ogden, J. M., Adelson, E. H., Bergen, J. R., and Burt, P. J.
RCA Engineer, 30(5):4-15 (1985).

Pyramid Methods in Image Processing
Adelson, E. H., Anderson, C. H., Bergen, J. R., Burt, P. J., and Ogden, J. M.
RCA Engineer, 29(6):33-41 (1984).

The Laplacian Pyramid as a Compact Image Code
Burt, P., and Adelson, E. H.
IEEE Transactions on Communication, COM-31:532-540 (1983).
A Multiresolution Spline with Application to Image Mosaics
Burt, P., and Adelson, E. H.
ACM Transactions on Graphics, 2(4):217-236 (1983). (portal color version)

Saliency and emphasis

Contextual guidance of eye movements and attention in real-world scenes: The role of global features on object search
Antonio Torralba, Aude Oliva, Monica Castelhano, John Henderson
Psychological Review, Vol. 113, No. 4. (October 2006), pp. 766-786.

De-Emphasis of Distracting Image Regions Using Texture Power Maps
Sara L. Su, Frédo Durand, and Maneesh Agrawala
Proc. of Texture 2005, Beijing, China, October 2005.

Human Learning of Contextual Priors for Object Search: Where does the time go?
B. Hidalgo-Sotelo, A. Oliva, and A. Torralba
Proceedings of the 3rd Workshop on Attention and Performance in Computer Vision at the Int. CVPR, 2005.
Contextual Influences on Saliency
A. Torralba
Neurobiology of Attention, Eds. L. Itti, G. Rees and J. Tsotsos. Pages 586-593. Academic Press / Elsevier. 2005
  Saliency, objects and scenes: global scene factors in attention and object detection
A. Torralba, A. Oliva, M. Castelhano and J. M. Henderson
Vision Sciences Society Annual Meeting, Sarasota. 2004.

Modeling global scene factors in attention
A. Torralba
Journal of Optical Society of America A. Special Issue on Bayesian and Statistical Approaches to Vision. Vol. 20(7): 1407-1418, 2003.
Top-down control of visual attention in object detection
A. Oliva, A. Torralba, M. S. Castelhano and J. M. Henderson
Proceedings of the IEEE International Conference on Image Processing. Vol. I, pages 253-256; September 14-17, in Barcelona, Spain, 2003.

Color and white balance

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

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

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
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

Non-Photorealistic styles

An Interactive Artificial Ant Approach to Non-Photorealistic Rendering
Yann Semet, Una-May O'Reilly, Frédo Durand
GECCO'04: Genetic and Evolutionary COmputation Conference

An Invitation to Discuss Computer Depiction
Frédo Durand
ACM/Eurographics Symp. NPAR'02.
Decoupling Strokes and High-Level Attributes for Interactive Traditional Drawing
Frédo Durand, Victor Ostromoukhov, Mathieu Miller, François Duranleau, and Julie Dorsey
in the Proceedings of the 12th Eurographics Workshop on Rendering, June 2001.

Hybrid images

Hybrid images
A. Oliva, A. Torralba and P. Schyns
SIGGRAPH, July 2006.


Related courses

6.088 Digital and Computational Photography
6.882 Advanced Computational Photography

see also 2006 offering

6.A44 Computational Photography

Freshman seminar

A Gentle Introduction to Bilateral Filtering and its Applications

SIGGRAPH 2007 Course.
Monday morning (8:30am - 12:15pm)

The Art and Science of Depiction (Spring 2001)

This class explores perceptual and technical aspect of pictures, and more precisely the depiction of reality on a 2D medium. The focus is on an in-breadth multidisciplinary approach. Here are the slides of a talk at the University College of London to outline the class. And here is a more recent version given at Stanford (1 slide per page or 6 slides per page)


Perceptual and Artistic Principles for Effective Computer Depiction

SIGGRAPH 2002 Course