Publications by Topic

Object Recognition / Scene Understanding

Deep Learning

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network,
Eigen, D., Puhrsch, C. and Fergus, R.
Proc. Neural Information Processing Systems 2014,
(9 pages PDF)

Learning to Discover Efficient Mathematical Identities,
Zaremba, W., Kurach, K. and Fergus, R.
Proc. Neural Information Processing Systems 2014,
(9 pages PDF)

Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation,
Denton, E., Zaremba, W., Bruna, J., LeCun, Y. and Fergus, R.
Proc. Neural Information Processing Systems 2014,
(9 pages PDF)

Visualizing and Understanding Convolutional Networks,
Zeiler, M. and Fergus, R.
Proc. of the IEEE European Conference on Computer Vision 2014,
(11 pages PDF)

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks,
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R. and LeCun, Y.
Proc. International Conference on Learning Representations 2014,
(16 pages PDF)

Intriguing Properties of Neural Networks,
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. and Fergus, R.
Proc. International Conference on Learning Representations 2014,
(10 pages PDF)

Understanding Deep Architectures using a Recursive Convolutional Network,
Eigen, D., Rolfe, J., Fergus, R. and LeCun, Y.
arXiv:1312.1847, Dec 2013,
(9 pages PDF)

Regularization of Neural Networks using DropConnect
Li, W., Zeiler, M., Zhang, S., LeCun, Y. and Fergus, R.
Proc. of the International Conference on Machine Learning 2013,
(10 pages PDF) | (Project page)

Stochastic Pooling for Regularization of Deep Convolutional Neural Networks,
Zeiler, M. and Fergus, R.
Proc. of the International Conference on Representation Learning 2013,
(8 pages PDF)

Differentiable Pooling for Hierarchical Feature Learning
Zeiler, M. and Fergus, R.
Technical Report, Arxiv (1207.0151v1)
(12 pages PDF)

Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
Matt Zeiler, Graham Taylor and Rob Fergus
Proc. of the IEEE Intl. Conf on Computer Vision 2011,
PDF | Project Page

Pose-sensitive embedding by non-linear NCA regression
Taylor, G., Fergus, R., Spiro, I., Williams, G. and Bregler, C.
Proc. Neural Information Processing Systems 2010,
(9 pages PDF) Supplementary material

Convolutional Learning of Spatio-Temporal Features
Taylor, G., Fergus, R., LeCun, Y. and Bregler, C.
Proc. of the IEEE European Conference on Computer Vision 2010,
(14 pages PDF) Supplementary material

Deconvolutional Networks
Zeiler, M., Krishnan, D., Taylor, G. and Fergus, R.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2010,
(8 pages PDF)

Learning Invariant Features through Topographic Filter Maps
Kavukcuoglu, K. , Ranzato, M. , Fergus, R. and LeCun, Y.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2009,
(8 pages PDF)

Compact Binary Codes

Multidimensional Spectral Hashing
Weiss, Y., Fergus, R. and Torralba, A.
Proc. of the IEEE European Conference on Computer Vision 2012,
(14 pages PDF)

Semi-supervised Learning in Gigantic Image Collections
Fergus, R., Weiss, Y. and Torralba, A.
Proc. Neural Information Processing Systems 2009,
(8 pages PDF)

Spectral Hashing
Weiss, Y., Torralba, A. and Fergus, R.
Proc. Neural Information Processing Systems 2008,
(8 pages PDF) (Project page)

Small Codes and Large Image Databases for Recognition
Torralba, A. , Fergus, R. and Weiss, Y.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2008,
(8 pages PDF), (Slides PPT), Google TechTalk Video (Link), Matlab Code (.zip)

Computational Photography

Depth Map Prediction from a Single Image using a Multi-Scale Deep Network,
Eigen, D., Puhrsch, C. and Fergus, R.
Proc. Neural Information Processing Systems 2014,
(9 pages PDF)

Blind Deconvolution with Re-weighted Sparsity Promotion,
Krishnan, D., Bruna, J. and Fergus, R.
arXiv 1311.4029, Nov 2013,
(16 pages PDF)

Restoring An Image Taken Through a Window Covered with Dirt or Rain,
Eigen, D., Krishnan, D. and Fergus, R.
Proc. of the IEEE International Conf. on Computer Vision (ICCV),
(8 pages PDF) (Project page)

Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines
Zeiler, M., Taylor, G., Sigal, L., Matthews, I. and Fergus, R.
Proc. Neural Information Processing Systems 2011,
(9 pages PDF)

Blind Deconvolution using a Normalized Sparsity Measure
Krishnan, D., Tay, T. and Fergus, R.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2011,
(8 pages PDF) Project page

Dark Flash Photography
Krishnan, D. and Fergus, R.
ACM Trans. on Graphics, (Proc. SIGGRAPH 2009).
(High Res (73Mb) - 11 pages PDF)
(Low Res (5.1Mb) - 11 pages PDF)
(Bibtex) (Project page)

Fast Image Deconvolution using Hyper-Laplacian Priors
Krishnan, D. and Fergus, R.
Proc. Neural Information Processing Systems 2009,
(8 pages PDF) (Project page)

Image and Depth from a Conventional Camera with a Coded Aperture
Levin, A., Fergus, R., Durand, F. and Freeman, W.T.
ACM Trans. on Graphics, (Proc. SIGGRAPH 2007).
(9 pages PDF) (Bibtex) (Project page)

Removing Camera Shake From A Single Photograph
Fergus, R., Singh, B., Hertzmann A., Roweis, S. T. and Freeman, W.T.
ACM Trans. on Graphics, Vol. 25, Issue 3, pp. 787-794, (Proc. SIGGRAPH 2006).
(8 pages PDF) (Bibtex) (Project page)

Random Lens Imaging
Fergus, R., Torralba A. and Freeman, W.T.
MIT CSAIL Technical Report 2006-058, 2006.
(11 pages PDF) (Bibtex)

Internet Vision

Learning Object Categories from Internet Image Searches
Fergus, R. , Fei-Fei L. , Perona, P. and Zisserman, A.
Proc. of IEEE, Vol. 98, No. 8, Special Issue on Internet Vision, August 2010.

Semi-supervised Learning in Gigantic Image Collections
Fergus, R., Weiss, Y. and Torralba, A.
Proc. Neural Information Processing Systems 2009,
(8 pages PDF)

Spectral Hashing
Weiss, Y., Torralba, A. and Fergus, R.
Proc. Neural Information Processing Systems 2008,
(8 pages PDF) (Project page)

80 million tiny images: a large dataset for non-parametric object and scene recognition
Torralba, A., Fergus, R. and Freeman, W.T.
IEEE PAMI, November 2008
(13 pages PDF) (Bibtex) (Project page)

Learning Object Categories from Google's Image Search
Fergus, R. , Fei-Fei L. , Perona, P. and Zisserman, A.
Proc. of the 10th Inter. Conf. on Computer Vision, ICCV 2005.
(8 pages PDF) (Bibtex) (Project Page)
Datasets used in this paper can be found here

A Visual Category Filter for Google Images
Fergus, R. , Perona, P. and Zisserman, A.
Proc. of the 8th European Conf. on Computer Vision, ECCV 2004.
(14 pages PDF) (Bibtex) (Project Page)

Object Recognition

Instance Segmentation of Indoor Scenes using a Coverage Loss,
Silberman, N., Sontag, D. and Fergus, R.
Proc. of the IEEE European Conference on Computer Vision 2014,
(14 pages PDF)?

Segmentation and Support Inference from RGBD Images'
Silberman, N., Hoiem, D., Kolhi, P. and Fergus, R.
Proc. of the IEEE European Conference on Computer Vision 2012,''
(14 pages PDF)

Nonparametric Image Parsing using Adaptive Neighbor Sets
Eigen, D. and Fergus, R.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2012,
(8 pages PDF) | (Code)

A Hybrid Neural Network-Latent Topic Model
Wan, L. and Zhu, L. and Fergus, R.
Proc. Intl. Conf. on Artificial Intelligence and Statistics 2012,
(8 pages PDF)

Indoor Scene Segmentation using a Structured Light Sensor
Nathan Silberman and Rob Fergus
ICCV 2011 Workshop on 3D Representation and Recognition,
PDF | Project Page

Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
Matt Zeiler, Graham Taylor and Rob Fergus
Proc. of the IEEE Intl. Conf on Computer Vision 2011,
PDF | Project Page

Learning Invarance through Imitation
Taylor, G., Spiro, I., Bregler, C. and Fergus, R.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2011,
(8 pages PDF) Supplementary material

Semantic Label Sharing for Learning with Many Categories
Fergus, R., Bernal, H., Weiss, Y. and Torralba, A.
Proc. of the IEEE European Conference on Computer Vision 2010,
(14 pages PDF)

Deconvolutional Networks
Zeiler, M., Krishnan, D., Taylor, G. and Fergus, R.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2010,
(8 pages PDF)

Object Recognition by Scene Alignment
Russell, B. , Torralba, A. , Liu, C. , Fergus, R. and Freeman, W.T.
Proc. Neural Information Processing Systems 2007.,
(8 pages PDF)

Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
Fergus, R. , Perona, P. and Zisserman, A.
International Journal of Computer Vision, Vol. 71(3), 273-303, March 2007
(47 pages PDF) (Bibtex) (Project page)

L. Fei-Fei, R. Fergus and P. Perona.
IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 28(4), 594 - 611, 2006
(18 pages PDF) (Bibtex)

A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
Fergus, R. , Perona, P. and Zisserman, A.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2005.
(8 pages PDF) (Bibtex) (Project page)

Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories
Fei-Fei, L. , Fergus, R. and Perona, P.
CVPR Workshop on Generative Model Based Vision, 2004.
(9 pages PDF) (Bibtex)

Object Class Recognition by Unsupervised Scale-Invariant Learning
Fergus, R. , Perona, P. and Zisserman, A.
Proc. of the IEEE Conf on Computer Vision and Pattern Recognition 2003.
(8 pages PDF) (Bibtex) (Project Page).
Datasets used in this paper can be found here and here.
Winner of CVPR 2003 Best Paper prize.

A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Fei-Fei, L. , Fergus, R. and Perona, P.\\ Proc. of the 9th Inter. Conf. on Computer Vision, ICCV 2003.
(8 pages PDF) (Bibtex)

Efficient Methods for Object Recognition using the Constellation Model
Fergus, R., Weber, M. and Perona, P.
Caltech Technical Report, 2001.
(8 pages PDF) (Bibtex)

Visual Object Category Recognition
Fergus, R.
D.Phil thesis, University of Oxford, 2005.
(193 pages PDF) (Bibtex)
Winner of the British Computer Society's 2006 Distinguished Dissertations award
(Best Computer Science thesis in the UK)
Winner of the British Machine Vision Association's 2006 Sullivan prize
(Best Computer Vision thesis in UK)

Applications

S4: A Spatial-Spectral model for Speckle Suppression,
Fergus, R., Hogg, D., Oppenheimer, B., Brenner, D. and Pueyo, L.
To Appear in the Astrophysical Journal,
(23 pages PDF)

Case for Automated Detection of Diabetic Retinopathy
Silberman, N., Ahlrich, K., Fergus, R. and Subramanian, L.,
AAAI Spring Symposium, 2010. (6 pages PDF)

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Publications by Topic

Full List By Year

Deep Learning

Compact Binary Codes

Computational Photography

Object Recognition / Scene Understanding

Internet Vision

Applications

Deep Learning

Compact Binary Codes

Computational Photography

Internet Vision

Object Recognition

Applications