M. Guillaumin, L. Van Gool and V. Ferrari

Fast Energy Minimization using Learned State Filters

IEEE Computer Vision and Pattern Recognition (CVPR), Portland, June 2013.

B. Alexe, N. Heess, Y.W. Teh and V. Ferrari

Searching for objects driven by context

Advances in Neural Information Processing Systems (NIPS), Nevada, USA, December 2012 (spotlight oral).

Sequences of hypotheses generated on Pascal VOC 2010

M. Eichner, V. Ferrari

Appearance Sharing for Collective Human Pose Estimation

Asian Conference on Computer Vision (ACCV), Daejeon, Korea, November 2012.

N. Jammalamadaka, A. Zisserman, M. Eichner, V. Ferrari, C. V. Jawahar

Has my Algorithm Succeeded? An Evaluator for Human Pose Estimators

European Conference on Computer Vision (ECCV), Firenze, Italy, October 2012.

D. Kuettel, M. Guillaumin, and V. Ferrari

Segmentation Propagation in ImageNet

European Conference on Computer Vision (ECCV), Firenze, Italy, October 2012. (BEST PAPER AWARD)

Spotlight video at ECCV12

Source code for segmentation transfer

Project page with data

Invited talk at Google

A. Prest, C. Schmid, and V. Ferrari

Weakly supervised learning of interactions between humans and objects

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), March 2012.

A. Prest, V. Ferrari, and C. Schmid

Explicit modeling of human-object interactions in realistic videos

IEEE Transactions on Pattern Analysis and Machine Intelligence 2012, in press

This publication is a revised version of the homonymous INRIA technical report that appeared in September 2011.

T. Deselaers, B. Alexe, and V. Ferrari

Weakly Supervised Localization and Learning with Generic Knowledge

International Journal of Computer Vision (IJCV), 100(3), p. 257-293, September 2012

This publication is a revised version of ETHZ technical report #275 that appeared in August 2011.

M. Eichner and V. Ferrari

Human Pose Co-Estimation and Applications

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 34(11), p. 2282-2288, November 2012.

This publication is a revised version of the homonymous ETHZ technical report #277 that appeared in November 2011.

Synchronic activities stickmen dataset.

D. Kuettel and V. Ferrari

Figure-ground segmentation by transferring window masks

IEEE Computer Vision and Pattern Recognition (CVPR), Providence, June 2012.

source code and data

M. Guillaumin and V. Ferrari

Large-scale Knowledge Transfer for Object Localization in ImageNet

IEEE Computer Vision and Pattern Recognition (CVPR), Providence, June 2012.

Project page with data

Invited talk at Google

A. Prest, C. Leistner, J. Civera, C. Schmid, and V. Ferrari

Learning Object Class Detectors from Weakly Annotated Video

IEEE Computer Vision and Pattern Recognition (CVPR), Providence, June 2012.

Youtube-Objects dataset

A.Vezhnevets, V. Ferrari, J. M. Buhmann

Weakly Supervised Structured Output Learning for Semantic Segmentation

IEEE Computer Vision and Pattern Recognition (CVPR), Providence, June 2012. (oral)

A.Vezhnevets, J. M. Buhmann, V. Ferrari

Active Learning for Semantic Segmentation with Expected Change

IEEE Computer Vision and Pattern Recognition (CVPR), Providence, June 2012.

N. Jammalamadaka, A. Zisserman, M. Eichner, V. Ferrari, C. V. Jawahar

Video Retrieval by Mimicking Poses

International Conference on Multimedia Retrieval (ICMR), Hong Kong, June 2012.

M. Eichner, M. Marin-Jimenez, A. Zisserman, V. Ferrari

2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images

International Journal of Computer Vision, (IJCV), 99(2), p. 190-214, September 2012

This publication is a revised version of the homonymous ETHZ technical report #272 that appeared in September 2010.

B. Alexe, T. Deselaers and V. Ferrari

Measuring the objectness of image windows

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 34(11), p. 2189-2202, November 2012.

Source code v1.5

D. Kuettel, M. Guillaumin, and V. Ferrari

Combining Image-Level and Segment-Level Models for Automatic Annotation

18th International Conference on MultiMedia Modelling (MMM), Klagenfurt, Austria, January, 2012. (oral)

B. Alexe, V. Petrescu, and V. Ferrari

Exploiting spatial overlap to efficiently compute appearance distances between image windows

Advances in Neural Information Processing Systems (NIPS), Granada, December 2011.

Supplementary material

Source code v1.0

A. Vezhnevets, V. Ferrari, and J. Buhmann

Weakly Supervised Semantic Segmentation with a Multi-image Model

International Conference on Computer Vision (ICCV), Barcelona, Spain, November 2011

M. Marin-Jimenez, A. Zisserman, and V. Ferrari

"Here's looking at you, kid" - Detecting people looking at each other in videos

British Machine Vision Conference (BMVC), Dundee, September 2011. (oral)

Data annotations

M. Ozcan, L. Jie, V. Ferrari, and B. Caputo

A Large-Scale Database of Images and Captions for Automatic Face Naming

British Machine Vision Conference (BMVC), Dundee, September 2011. (oral)

FAN-Lage database of 125000 images and captions

L. Jie, O. Francesco, C. Barbara, and V. Ferrari

Learning from Images with Captions Using the Maximum Margin Set Algorithm

IDIAP Research Report #30, August 2011 (submitted to PAMI).

T. Deselaers and V. Ferrari

Visual and Semantic Similarity in ImageNet

IEEE Computer Vision and Pattern Recognition (CVPR), Colorado Springs, June 2011.

T. Deselaers, B. Alexe, and V. Ferrari

"Localizing Objects while Learning Their Appearance"

European Conference on Computer Vision (ECCV), Crete, Greece, September 2010. (oral)
This publication is also ETH technical report #274.

B. Alexe, T. Deselaers, and V. Ferrari

"ClassCut for Unsupervised Class Segmentation"

European Conference on Computer Vision (ECCV), Crete, Greece, September 2010.

M. Eichner and V. Ferrari

"We Are Family: Joint Pose Estimation of Multiple Persons"

European Conference on Computer Vision (ECCV), Crete, Greece, September 2010.

supplementary material

Dataset

T. Deselaers and V. Ferrari

"A Conditional Random Field for Multiple-Instance Learning"

International Conference on Machine Learning (ICML), Haifa, Israel, June 2010.

Paper discussion site

"What is an object?"

IEEE Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010.

Source code v1.5

D. Kuettel, M. Breitenstein, L. van Gool, and V. Ferrari

"What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes"

IEEE Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010. (oral)

Video of the talk at CVPR 2010
slides (powerpoint, with animations)
slides (pdf, without animations)

The code and data is available.

An article about this work in the eth life magazine available in english
and german.

A short article in the german M.I.T. magazine of 2010/8, see preview or original content (paywalled).

T. Deselaers and V. Ferrari

"Global and Efficient Self-Similarity for Object Classification and Detection"

IEEE Computer Vision and Pattern Recognition (CVPR), San Francisco, June 2010. (oral)

Video of the talk at CVPR 2010

Code available

B. Alexe, T. Deselaers, M. Eichner, V. Ferrari, P. Gehler, A. Lehmann, S. Pellegrini, A. Prest

"Which Energy Minimization for my MRF/CRF? A Cheat-Sheet"

Computer Vision Laboratory, ETH Zurich, Technical Report 273

V. Ferrari, F. Jurie, and C. Schmid

"From Images to Shape Models for Object Detection"

International Journal of Computer Vision (IJCV), March 2010.

Learning explicit shape models from unsegmented training images, and using them to localize object outlines in novel test images.

Performance plots available as Matlab figures

Matlab source code v1.3

This publication is a revised version of the homonymous INRIA technical report appeared in July 2008 (now obsolete and no longer available).

L. Jie, B. Caputo, and V. Ferrari

"Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation"

Advances in Neural Information Processing Systems (NIPS), Vancouver, December 2009.

Associating persons' faces and poses in news images to names and verbs in their captions.

M. Eichner and V. Ferrari

"Better Appearance Models for Pictorial Structures"

British Machine Vision Conference (BMVC), London, September 2009. (oral)

Estimating body part appearance models from a single image of an unknown person.

ETHZ PASCAL Stickmen dataset of annotated 2D human poses

Pose estimation results

Matlab source code

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, L. Van Gool

"Using Multi-view Recognition to Guide a Robot's attention"

International Journar of Robotics Research (IJRR), August 2009.

Multi-view object class detection and meta-data inference (this journal paper is an extended version of our CVPR 2006 and RSS 2008 papers)

V. Ferrari, M. Marin, and A. Zisserman

"2D Human Pose Estimation in TV Shows"

Dagstuhl post-proceedings, 2009.

Fully automatic 2D human pose estimation in uncontrolled video. This is an extension of our CVPR 2008 paper.

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, L. Van Gool

"Shape-from-recognition: Recognition enables meta-data transfer"

Computer Vision and Image Understanding (CVIU), December 2009.

Inferring meta-data, such as depth, surface normals, and part decomposition from a single image of an object, using cognitive feeback from recognition (this journal paper is an extended version of our 3dRR 2007 paper)

V. Ferrari, M. Marin, and A. Zisserman

"Pose Search: retrieving people using their pose"

IEEE Computer Vision and Pattern Recognition (CVPR), Miami, June 2009. (oral)

Retrieving shots containing a particular human pose from movies and TV videos.

Buffy Pose Classes dataset for pose search

Showcase page

V. Ferrari, M. Marin, and A. Zisserman

"Progressive Search Space Reduction for Human Pose Estimation"

IEEE Computer Vision and Pattern Recognition (CVPR), Alaska, June 2008.

Fully automatic 2D human pose estimation in uncontrolled video (Buffy the Vampire Slayer!).

Buffy Stickmen dataset of annotated 2D human poses

Software for detecting and tracking human upper-bodies

Showcase page

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, L. Van Gool

"Using Recognition to Guide a Robot's Attention"

Robotics: Science and Systems Conference (RSS), Zurich, Switzerland, June 2008. (oral)

Recognizing objects of interest for a robot, and localizing interaction points

V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid

"Groups of Adjacent Contour Segments for Object Detection"

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), January 2008

A new family of local contour features and their application to object class detection.

Matlab source code v1.04

Source code available on request

Performance plots available as Matlab figures

This publication is a revised version of the homonymous INRIA technical report appeared in September 2006 (now obsolete and no longer available).

V. Ferrari and A. Zisserman

"Learning Visual Attributes"

Advances in Neural Information Processing Systems (NIPS), Vancouver, December 2007 (spotlight)

Dataset

Showcase page

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, and L. Van Gool

"Depth-From-Recognition: Inferring Meta-data by Cognitive Feedback"

3D Representation for Recognition (3dRR) - Workshop in conjunction with International Conference on Computer Vision (ICCV), Rio de Janeiro, Brasil, October 2007

Inferring 3D depth from a single image of an object, using cognitive feeback from recognition

T. Quack, V. Ferrari, B. Leibe, and L. Van Gool

"Efficient Mining of Frequent and Distinctive Feature Configurations"

International Conference on Computer Vision (ICCV), Rio de Janeiro, Brasil, October 2007

Feature selection for object class detection, by efficient mining of frequent and distinctive spatial feature configurations

J. Philbin, O. Chum, J. Sivic, V. Ferrari, M. Marin, A. Bosch, N. Apostolof, and A. Zisserman

"Oxford TRECVid 2007 - Notebook paper"

V. Ferrari, F. Jurie, and C. Schmid

"Accurate Object Detection with Deformable Shape Models Learnt from Images"

IEEE Computer Vision and Pattern Recognition (CVPR), Minneapolis, June 2007.

Performance plots available as Matlab figures

Matlab source code v1.3

V. Ferrari, T. Tuytelaars, and L. Van Gool

"Simultaneous Object Recognition and Segmentation by Image Exploration"

Lecture notes in computer science, vol. 4170, (Toward category-level object recognition, eds. J. Ponce, M. Hebert, C. Schmid, and A. Zisserman), pp. 151-178, 2006

Book chapter in a survey of state-of-the-art object recognition methods.

Source code v1.1

T. Quack, V. Ferrari, and L. Van Gool

"Video Mining with Frequent Itemset Configurations"

International Conference on Image and Video Retrieval (CIVR), Arizona, July 2006.

A. Thomas, V. Ferrari, B. Leibe, T. Tuytelaars, B. Schiele, and L. Van Gool

"Towards Multi-View Object Class Detection"

IEEE Computer Vision and Pattern Recognition (CVPR), New York, June 2006.

Multi-view object class detection by combining my Image Exploration technique with Leibe`s Implict Shape Model.

V. Ferrari, T. Tuytelaars, and L. Van Gool

"Object Detection by Contour Segment Networks"

European Conference on Computer Vision (ECCV), Graz, May 2006. (oral)

Detecting object classes in real images, given a single hand-drawn example as model of their shape.

Performance plots available as Matlab figures

ETHZ Shape Classes v1.2 dataset (including our performance plots as matlab figures)

V. Ferrari, T. Tuytelaars, and L. Van Gool

"Simultaneous Object Recognition and Segmentation from Single or Multiple Model Views"

International Journal of Computer Vision (IJCV), April 2006

Special issue with extended versions of 5 papers selected from ECCV 2004; also includes material from the CVPR 2004 paper.

Source code v1.1

H. Bay, V. Ferrari, L. Van Gool

"Wide-baseline Stereo Matching with Line Segments"

IEEE Computer Vision and Pattern Recognition (CVPR), San Diego, USA, June 2005

A. Zalesny, V. Ferrari, G. Caenen, and L. Van Gool

"Composite Texture Synthesis"

International Journal of Computer Vision (IJCV), 62:1-2, pp. 161-176, April 2005

Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool

"Retrieving Objects From Videos Based on Affine Regions"

European Signal Processing conference (EUSIPCO), Vienna, Austria, September 2004 (oral)

Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool

"Integrating Multiple Model Views for Object Recognition"

IEEE Computer Vision and Pattern Recognition (CVPR), Washington, USA, June 2004

Source code v1.1

Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool

"Simultaneous Object Recognition and Segmentation by Image Exploration"

European Conference on Computer Vision (ECCV), Prague, May 2004. (oral)

ETHZ Toys dataset

Source code v1.1

H. Shao, T. Svoboda, V. Ferrari, T. Tuytelaars, L. Van Gool

"Fast indexing for image retrieval based on local appearance with re-ranking"

International Conference on Image Processing (ICIP), September 2003. (oral)

Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool

"Wide-baseline muliple-view Correspondences"

IEEE Computer Vision and Pattern Recognition (CVPR), Madison, USA, June 2003

L. Van Gool, T. Tuytelaars, V. Ferrari, C. Strecha, J. Vanden Wyngaerd and M. Vergauwen

"3D Modeling and Registration Under Wide Baseline Conditions"

Proc. ISPRS Commission III, Vol.~34, Part 3A, Photogrammetric Computer Vision (PCV), Graz, September 2002, pp.~3-14

Invited Keynote speech

Alexey Zalesny, Vittorio Ferrari, Geert Caenen, Dominik Auf der Maur, and Luc Van Gool

"Composite Texture Descriptions"

European Conference on Computer Vision (ECCV), Copenhagen, Danemark, May 2002, Vol. 3, pp. 180-194

Geert Caenen, Vittorio Ferrari, Alexey Zalesny, and Luc Van Gool

"Analyzing the layout of composite textures"

Texture 2002 Workshop in conjunction with ECCV, Copenhagen, Danemark, May 2002, pp. 15-19.

Alexey Zalesny, Vittorio Ferrari, Geert Caenen, and Luc Van Gool

"Parallel Composite Texture Synthesis"

Texture 2002 Workshop in conjunction with ECCV, Copenhagen, Danemark, May 2002, pp. 151-155.

Vittorio Ferrari, Tinne Tuytelaars and Luc Van Gool

"Real-time Affine Region Tracking and Coplanar Grouping"

in Proc. of the IEEE Computer Vision and Pattern Recognition (CVPR), Kauai, Hawaii, December 2001.

Vittorio Ferrari, Tinne Tuytelaars and Luc Van Gool

"Markerless Augmented Reality with a Real-time Affine Region Tracker"

in Proc. of the IEEE and ACM International Symposium on Augmented Reality (ISAR), New York, New York, October 2001, pp. 87-96 (oral)