Primary Subject Area: 3D computer vision | |
| • Adrian Hilton University of Surrey, UK |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction 3D computer vision\Scene analysis from depth cameras Face and gesture\Body motion analysis Motion and tracking\Model-based reconstruction and tracking Vision for X\Vision for graphics |
| • Adrien Bartoli Universite d'Auvergne, France |
Secondary Subject Area(s): Biomedical image analysis\Biomedical image registration Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Motion and tracking\Image alignment and registration |
| • Hideo Saito Keio University, Japan |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Photometric modeling Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Low-level vision and image processing\De-blurring and super-resolution Motion and tracking\Model-based reconstruction and tracking Motion and tracking\Object tracking and motion analysis |
| • Hongdong Li Australian National University, Australia |
Secondary Subject Area(s): 3D computer vision\Structure from motion Motion and tracking Optimization methods Video: events, activities and surveillance\Video segmentation |
| • Konrad Schindler ETH Zurich, Switzerland |
Secondary Subject Area(s): Motion and tracking\Optical flow Recognition: detection, categorization, indexing, matching\Scene understanding Segmentation, grouping and shape representation\Semantic image segmentation |
| • Long Quan Hong Kong University of Science and Technology, Hong Kong |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction 3D computer vision\Calibration and pose estimation 3D computer vision\Scene analysis from depth cameras 3D computer vision\Stereo 3D computer vision\Structure from motion |
| • PJ Narayanan International Institute of Information Technology, Hyderabad, India |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction 3D computer vision\Structure from motion Computational photography, photometry, shape from X\Sensors, cameras and displays Vision for X\Vision for graphics Vision for X\Vision for robotics |
| • Reinhard Klette Auckland University of Technology, New Zealand |
Secondary Subject Area(s): Face and gesture\Face detection and head tracking Segmentation, grouping and shape representation\Semantic image segmentation Vision for X\Vision for robotics |
| • Reinhard Koch University of Kiel, Germany |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Motion and tracking Vision for X\Vision for graphics Vision for X\Vision for robotics |
| • Sameer Agarwal Google, Seattle, USA |
Secondary Subject Area(s): Optimization methods |
| • Takayuki Okatani Tohoku University, Japan |
Secondary Subject Area(s): Computational photography, photometry, shape from X Optimization methods Recognition: detection, categorization, indexing, matching\Attributes Statistical methods and learning\Deep learning and convolutional neural networks Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
| • Yasutaka Furukawa Washington University, St. Louis, USA |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture |
Primary Subject Area: 3D computer vision\3D modeling and reconstruction | |
| • Ian Reid University of Adelaide, Australia |
Secondary Subject Area(s): 3D computer vision\Structure from motion Motion and tracking\Object tracking and motion analysis Recognition: detection, categorization, indexing, matching\Scene understanding |
Primary Subject Area: 3D computer vision\Structure from motion | |
| • Keinichi Kanatani Okayama University, Japan |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction 3D computer vision\Calibration and pose estimation |
Primary Subject Area: Biomedical image analysis | |
| • Baba Vemuri University of Florida Miami, USA |
Secondary Subject Area(s): Biomedical image analysis\Biomedical image registration Biomedical image analysis\Biomedical image segmentation Biomedical image analysis\Computational anatomy Motion and tracking\Image alignment and registration Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
Primary Subject Area: Biomedical image analysis\Biomedical image registration | |
| • Nassir Navab Johns Hopkins (USA) and TU Munich (Germany) |
Secondary Subject Area(s): Biomedical image analysis\Biomedical image segmentation Face and gesture\Body motion analysis Motion and tracking\Image alignment and registration |
Primary Subject Area: Computational photography, photometry, shape from X | |
| • Jingyi Yu University of Delaware, USA |
Secondary Subject Area(s): 3D computer vision Low-level vision and image processing Vision for X\Vision for graphics |
| • Ko Nishino Drexel University, USA |
Secondary Subject Area(s): Motion and tracking\People tracking Segmentation, grouping and shape representation\Shape representation and matching Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Video surveillance Vision for X\Vision for graphics |
| • Kristin Dana Rutgers University, USA |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Photometric modeling Computational photography, photometry, shape from X\Sensors, cameras and displays Segmentation, grouping and shape representation\Image segmentation |
| • William Freeman MIT, USA |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Low-level vision and image processing Statistical methods and learning\Bayesian modeling Vision for X\Vision for graphics |
| • Yoav Schechner Technion Haifa, Israel |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Photometric modeling Computational photography, photometry, shape from X\Sensors, cameras and displays Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture |
Primary Subject Area: Computational photography, photometry, shape from X\Photometric modeling | |
| • Imari Sato National Institute of Informatics, Japan |
Secondary Subject Area(s): Computational photography, photometry, shape from X Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Low-level vision and image processing\Texture analysis and synthesis Vision for X\Vision for graphics |
Primary Subject Area: Computational photography, photometry, shape from X\Sensors, cameras and displays | |
| • Irfan Essa Georgia Institute of Technology, USA |
Secondary Subject Area(s): Motion and tracking\Image alignment and registration Recognition: detection, categorization, indexing, matching\Context Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Semantic video segmention Video: events, activities and surveillance\Video segmentation |
Primary Subject Area: Face and gesture | |
| • Aleix Martinez Ohio State University, USA |
Secondary Subject Area(s): 3D computer vision\Structure from motion Recognition: detection, categorization, indexing, matching\Person and face detection Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering Statistical methods and learning\Kernel methods |
| • Arun Ross Michigan State University, USA |
Secondary Subject Area(s): Face and gesture\Biometrics Face and gesture\Face recognition |
| • Ioannis Kakadiaris University of Houston, USA |
Secondary Subject Area(s): Biomedical image analysis |
| • Rogerio Feris IBM T.J. Watson Research Center, USA |
Secondary Subject Area(s): Face and gesture\Face detection and head tracking Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Person and face detection Video: events, activities and surveillance\Video surveillance |
| • Javier Ruiz del Solar University of Chile, Chile |
Secondary Subject Area(s): Face and gesture\Face detection and head tracking Face and gesture\Face recognition Face and gesture\Human identification Low-level vision and image processing\Feature extraction and matching Vision for X\Vision for robotics |
Primary Subject Area: Face and gesture\Face detection and head tracking | |
| • Nicu Sebe University of Trento, Italy |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Human pose estimation Recognition: detection, categorization, indexing, matching\Image indexing and retrieval Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Semantic video segmention Video: events, activities and surveillance\Video indexing and retrieval |
Primary Subject Area: Face and gesture\Face recognition | |
| • Lior Wolf Tel Aviv University, Israel |
Secondary Subject Area(s): Face and gesture\Biometrics Face and gesture\Gesture analysis Recognition: detection, categorization, indexing, matching\Images and language Statistical methods and learning\Deep learning and convolutional neural networks Vision for X\Document analysis |
| • Maja Pantic Imperial College London, UK |
Secondary Subject Area(s): Face and gesture\Biometrics Face and gesture\Face detection and head tracking Face and gesture\Gesture analysis Recognition: detection, categorization, indexing, matching\Person and face detection Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
| • Rama Chellappa University of Maryland, USA |
Secondary Subject Area(s): Face and gesture\Face detection and head tracking Motion and tracking\Object tracking and motion analysis Segmentation, grouping and shape representation\Image segmentation Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering Video: events, activities and surveillance\Events, actions and activity recognition |
Primary Subject Area: Low-level vision and image processing | |
| • ChiKeung Tang The Hong Kong University of Science and Technology, Hong Kong |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction Computational photography, photometry, shape from X\Photometric modeling Low-level vision and image processing\Texture analysis and synthesis Recognition: detection, categorization, indexing, matching\Large scale visual recognition Vision for X\Vision for graphics |
| • Eli Shechtman Adobe, Seattle, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching |
| • Michael Brown National University of Singapore, Singapore |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Sensors, cameras and displays Low-level vision and image processing\Color processing Low-level vision and image processing\De-blurring and super-resolution Low-level vision and image processing\Image enhancement and restoration |
| • Narendra Ahuja University of Illinois at Urbana-Champaign, USA |
Secondary Subject Area(s): 3D computer vision\Calibration and pose estimation Motion and tracking\People tracking Segmentation, grouping and shape representation\Image segmentation |
| • Stephen Lin Microsoft Research Asia, China |
Secondary Subject Area(s): Computational photography, photometry, shape from X Vision for X\Vision for graphics |
| • Yu-Wing Tai Korea Advanced Institute of Science and Technology, Korea |
Secondary Subject Area(s): 3D computer vision Computational photography, photometry, shape from X Motion and tracking Optimization methods Vision for X |
| • Zhouchen Lin Peking University, China |
Secondary Subject Area(s): Optimization methods Segmentation, grouping and shape representation Statistical methods and learning |
Primary Subject Area: Low-level vision and image processing\Color processing | |
| • Joost van de Weijer Universitat Autonoma de Barcelona, Spain |
Secondary Subject Area(s): Low-level vision and image processing\Biologically-inspired vision Low-level vision and image processing\Edge and contour detection Recognition: detection, categorization, indexing, matching\Feature extraction and description Recognition: detection, categorization, indexing, matching\Scene and image classification Segmentation, grouping and shape representation\Semantic image segmentation |
Primary Subject Area: Low-level vision and image processing\De-blurring and super-resolution | |
| • Paolo Favaro Bern University, Switzerland |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Optimization methods Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Statistical methods and learning\Deep learning and convolutional neural networks |
Primary Subject Area: Motion and tracking | |
| • Ahmed Elgammal Rutgers University, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Images and language Video: events, activities and surveillance |
| • Bohyung Han POSTECH, Pohang, Korea |
Secondary Subject Area(s): Segmentation, grouping and shape representation\Image segmentation Segmentation, grouping and shape representation\Semantic image segmentation Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Video segmentation Video: events, activities and surveillance\Video surveillance |
| • Ce Liu Google, Cambridge, USA |
Secondary Subject Area(s): Low-level vision and image processing Recognition: detection, categorization, indexing, matching\Image indexing and retrieval Recognition: detection, categorization, indexing, matching\Scene and image classification Recognition: detection, categorization, indexing, matching\Scene understanding Segmentation, grouping and shape representation\Semantic image segmentation |
| • David Suter University of Adelaide, Australia |
Secondary Subject Area(s): Segmentation, grouping and shape representation Segmentation, grouping and shape representation\Image segmentation Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Video segmentation Video: events, activities and surveillance\Video surveillance |
| • MingHsuan Yang UC Merced, USA |
Secondary Subject Area(s): Computational photography, photometry, shape from X Face and gesture Low-level vision and image processing Segmentation, grouping and shape representation Statistical methods and learning |
| • Octavia Camps Northeastern University, USA |
Secondary Subject Area(s): Face and gesture Optimization methods Segmentation, grouping and shape representation Statistical methods and learning Video: events, activities and surveillance |
| • Ying Wu Northwestern University, USA |
Secondary Subject Area(s): Face and gesture Low-level vision and image processing Recognition: detection, categorization, indexing, matching Statistical methods and learning Video: events, activities and surveillance |
Primary Subject Area: Motion and tracking\Optical flow | |
| • Thomas Brox University of Freiburg, Germany |
Secondary Subject Area(s): Low-level vision and image processing\Image enhancement and restoration Optimization methods\PDEs and variational methods Recognition: detection, categorization, indexing, matching\3D representations for recognition Statistical methods and learning\Deep learning and convolutional neural networks Video: events, activities and surveillance\Video segmentation |
Primary Subject Area: Optimization methods | |
| • Thomas Pock Graz University of Technology, Austria |
Secondary Subject Area(s): 3D computer vision\Stereo Low-level vision and image processing\De-blurring and super-resolution Low-level vision and image processing\Denoising Motion and tracking\Optical flow Segmentation, grouping and shape representation\Image segmentation |
Primary Subject Area: Optimization methods\Discrete optimization | |
| • Hiroshi Ishikawa Waseda University, Japan |
Secondary Subject Area(s): 3D computer vision\Stereo Segmentation, grouping and shape representation\Edge and contour analysis Segmentation, grouping and shape representation\Image segmentation |
| • Olga Veksler University of Western Ontario, Canada |
Secondary Subject Area(s): 3D computer vision\Stereo Segmentation, grouping and shape representation\Image segmentation |
| • Vladimir Kolmogorov Institute of Science and Technology, Austria |
Secondary Subject Area(s): Optimization methods\Inference in graphical models |
Primary Subject Area: Optimization methods\Inference in graphical models | |
| • Nikos Komodakis Ecole des Ponts ParisTech, France |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Object class detection and recognition Statistical methods and learning\Deep learning and convolutional neural networks |
| • Tomas Werner Czech Technical University, Czech Republic |
Secondary Subject Area(s): Optimization methods\Continuous optimization Optimization methods\Discrete optimization |
Primary Subject Area: Optimization methods\Sparse coding and dictionaries | |
| • Guillermo Sapiro Duke University, USA |
Secondary Subject Area(s): Low-level vision and image processing\De-blurring and super-resolution Low-level vision and image processing\Denoising Low-level vision and image processing\Image enhancement and restoration Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
| • John Wright Columbia University, USA |
Secondary Subject Area(s): Optimization methods\Continuous optimization Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
| • Julien Mairal INRIA, Grenoble, France |
Secondary Subject Area(s): Low-level vision and image processing\Denoising Optimization methods\Continuous optimization Optimization methods\Large scale optimization methods Statistical methods and learning\Kernel methods Statistical methods and learning\Large scale learning methods |
Primary Subject Area: Recognition: detection, categorization, indexing, matching | |
| • Abhinav Gupta Carnegie Mellon University, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Images and language Recognition: detection, categorization, indexing, matching\Large scale visual recognition Recognition: detection, categorization, indexing, matching\Scene understanding Statistical methods and learning\Semi-supervised learning |
| • Alex Berg University of North Carolina, USA |
Secondary Subject Area(s): 3D computer vision |
| • Allen Yang UC Berkeley, USA |
Secondary Subject Area(s): 3D computer vision Face and gesture Motion and tracking Optimization methods |
| • Arnold Smeulders University of Amsterdam, Netherlands |
Secondary Subject Area(s): Motion and tracking\Object tracking and motion analysis Recognition: detection, categorization, indexing, matching\Image indexing and retrieval Recognition: detection, categorization, indexing, matching\Instance detection and recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Recognition: detection, categorization, indexing, matching\Scene and image classification |
| • Aude Oliva MIT, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Context Recognition: detection, categorization, indexing, matching\Large scale visual recognition Recognition: detection, categorization, indexing, matching\Scene and image classification Recognition: detection, categorization, indexing, matching\Scene understanding |
| • David Forsyth University of Illinois at Urbana-Champaign, USA |
Secondary Subject Area(s): Computational photography, photometry, shape from X\Shape from focus, refraction, shading, specularities, shadows, texture Face and gesture\Body motion analysis Optimization methods\Continuous optimization Video: events, activities and surveillance\Video and language Vision for X\Vision for graphics |
| • Devi Parikh Virginia Tech, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Context Recognition: detection, categorization, indexing, matching\Images and language Recognition: detection, categorization, indexing, matching\Scene understanding |
| • Fatih Porikli ANU / NICTA, Australia |
Secondary Subject Area(s): Low-level vision and image processing\De-blurring and super-resolution Low-level vision and image processing\Image enhancement and restoration Motion and tracking Statistical methods and learning\Deep learning and convolutional neural networks Video: events, activities and surveillance |
| • James Hays Brown University, USA |
Secondary Subject Area(s): Low-level vision and image processing\De-blurring and super-resolution Low-level vision and image processing\Image enhancement and restoration Low-level vision and image processing\Texture analysis and synthesis Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Scene and image classification |
| • Jianxin Wu Nanjing University, China |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Feature extraction and description Recognition: detection, categorization, indexing, matching\Fine-grained recognition Recognition: detection, categorization, indexing, matching\Scene and image classification Statistical methods and learning\Kernel methods Video: events, activities and surveillance\Events, actions and activity recognition |
| • Joachim Denzler FSU Jena, Germany |
Secondary Subject Area(s): Low-level vision and image processing Motion and tracking\Object tracking and motion analysis Recognition: detection, categorization, indexing, matching\Fine-grained recognition Segmentation, grouping and shape representation\Semantic image segmentation Video: events, activities and surveillance\Events, actions and activity recognition |
| • Kate Saenko University of Massachusetts Lowel, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Statistical methods and learning\Deep learning and convolutional neural networks Statistical methods and learning\Transfer learning Video: events, activities and surveillance\Video and language |
| • Leonid Sigal Disney Research, Piitsburgh, USA |
Secondary Subject Area(s): Motion and tracking\People tracking Optimization methods\Inference in graphical models Statistical methods and learning Video: events, activities and surveillance\Events, actions and activity recognition Video: events, activities and surveillance\Video and language |
| • Lorenzo Torresani Darthmout College, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Large scale visual recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Statistical methods and learning\Deep learning and convolutional neural networks Video: events, activities and surveillance\Events, actions and activity recognition |
| • Mario Fritz MPI, Saarbrucken, Germany |
Secondary Subject Area(s): Statistical methods and learning Vision for X |
| • Nuno Vasconcelos UC San Diego, USA |
Secondary Subject Area(s): Low-level vision and image processing\Biologically-inspired vision Motion and tracking\Object tracking and motion analysis Recognition: detection, categorization, indexing, matching\Context Statistical methods and learning\Deep learning and convolutional neural networks Video: events, activities and surveillance\Events, actions and activity recognition |
| • Pietro Perona California Institute of Technology, USA |
Secondary Subject Area(s): Face and gesture Video: events, activities and surveillance |
| • Piotr Dollar Facebook AI Research, Menlo Park, USA |
Secondary Subject Area(s): Segmentation, grouping and shape representation |
| • Silvio Savarese Stanford University, USA |
Secondary Subject Area(s): 3D computer vision\Scene analysis from depth cameras Motion and tracking\People tracking Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Scene understanding Video: events, activities and surveillance\Events, actions and activity recognition |
| • Song-Chun Zhu UCLA, USA |
Secondary Subject Area(s): Optimization methods\Inference in graphical models Optimization methods\Sparse coding and dictionaries Segmentation, grouping and shape representation Statistical methods and learning\Unsupervised learning Video: events, activities and surveillance\Events, actions and activity recognition |
| • Victor Lempitsky Skolkovo Institute of Science and Technology, Russia |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Feature matching and indexing Recognition: detection, categorization, indexing, matching\Fine-grained recognition Recognition: detection, categorization, indexing, matching\Instance detection and recognition Recognition: detection, categorization, indexing, matching\Large scale visual recognition Statistical methods and learning\Deep learning and convolutional neural networks |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Feature extraction and description | |
| • Krystian Mikolajczyk University of Surrey, UK |
Secondary Subject Area(s): Low-level vision and image processing\Feature extraction and matching Motion and tracking\Object tracking and motion analysis |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Human pose estimation | |
| • Juergen Gall University of Bonn, Germany |
Secondary Subject Area(s): Face and gesture\Body motion analysis Face and gesture\Gesture analysis Motion and tracking\Model-based reconstruction and tracking Recognition: detection, categorization, indexing, matching\Object class detection and recognition Video: events, activities and surveillance\Events, actions and activity recognition |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Image indexing and retrieval | |
| • Herve Jegou INRIA, Rennes, France |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Feature matching and indexing Recognition: detection, categorization, indexing, matching\Instance detection and recognition Recognition: detection, categorization, indexing, matching\Large scale visual recognition |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Images and language | |
| • Larry Zitnick Microsoft Research Redmond, USA |
Secondary Subject Area(s): Low-level vision and image processing\Edge and contour detection Low-level vision and image processing\Feature extraction and matching Recognition: detection, categorization, indexing, matching\Feature extraction and description Recognition: detection, categorization, indexing, matching\Instance detection and recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Object class detection and recognition | |
| • Ales Leonardis University of Birmingham, UK |
Secondary Subject Area(s): Motion and tracking\Object tracking and motion analysis Vision for X\Vision for robotics |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Person and face detection | |
| • Dariu Gavrila Daimler Research & Development, Germany |
Secondary Subject Area(s): Face and gesture\Body motion analysis Motion and tracking\People tracking Recognition: detection, categorization, indexing, matching\Human pose estimation Vision for X\Vision for robotics |
Primary Subject Area: Recognition: detection, categorization, indexing, matching\Scene understanding | |
| • Charless Fowlkes University of California, Irvine, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Context Recognition: detection, categorization, indexing, matching\Object class detection and recognition Segmentation, grouping and shape representation\Grouping Segmentation, grouping and shape representation\Image segmentation |
| • Pushmeet Kohli Microsoft Research, UK |
Secondary Subject Area(s): 3D computer vision\Scene analysis from depth cameras 3D computer vision\Structure from motion Optimization methods\Inference in graphical models Segmentation, grouping and shape representation\Semantic image segmentation Statistical methods and learning\Deep learning and convolutional neural networks |
Primary Subject Area: Segmentation, grouping and shape representation | |
| • Cristian Sminchisescu Lund University, Sweden |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching |
| • Greg Shakhnarovich TTI Chicago, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching Statistical methods and learning |
| • Jianbo Shi University of Pennsylvania, USA |
Secondary Subject Area(s): 3D computer vision\Stereo Face and gesture\Body motion analysis Low-level vision and image processing\Edge and contour detection Motion and tracking\People tracking Video: events, activities and surveillance\Events, actions and activity recognition |
| • Kaleem Siddiqi McGill University, Canada |
Secondary Subject Area(s): Biomedical image analysis Optimization methods\PDEs and variational methods Recognition: detection, categorization, indexing, matching |
| • Pablo Arbelaez Universidad de los Andes, Colombia |
Secondary Subject Area(s): Biomedical image analysis\Biomedical image segmentation Low-level vision and image processing\Edge and contour detection Recognition: detection, categorization, indexing, matching\Object class detection and recognition Segmentation, grouping and shape representation\Image segmentation Segmentation, grouping and shape representation\Semantic image segmentation |
| • Xiaofeng Ren Amazon, USA |
Secondary Subject Area(s): Motion and tracking Recognition: detection, categorization, indexing, matching |
Primary Subject Area: Segmentation, grouping and shape representation\Grouping | |
| • Sven Dickinson University of Toronto, Canada |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Feature matching and indexing Recognition: detection, categorization, indexing, matching\Images and language Recognition: detection, categorization, indexing, matching\Object class detection and recognition Segmentation, grouping and shape representation\Shape representation and matching |
Primary Subject Area: Segmentation, grouping and shape representation\Shape representation and matching | |
| • Anuj Srivastava Florida State University, USA |
Secondary Subject Area(s): Biomedical image analysis\Biomedical image registration Biomedical image analysis\Computational anatomy Recognition: detection, categorization, indexing, matching\3D representations for recognition Segmentation, grouping and shape representation\Edge and contour analysis Statistical methods and learning\Dimensionality reduction, matrix factorization, manifold learning, manifold clustering |
Primary Subject Area: Statistical methods and learning | |
| • Barbara Caputo University of Rome La Sapienza, Italy |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Images and language Recognition: detection, categorization, indexing, matching\Large scale visual recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Recognition: detection, categorization, indexing, matching\Scene and image classification |
| • Erik Sudderth Brown University, USA |
Secondary Subject Area(s): Motion and tracking Optimization methods\Inference in graphical models Recognition: detection, categorization, indexing, matching Statistical methods and learning\Semi-supervised learning Statistical methods and learning\Unsupervised learning |
| • Francois Fleuret IDIAP, Switzerland |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Feature extraction and description Statistical methods and learning\Deep learning and convolutional neural networks Statistical methods and learning\Semi-supervised learning Statistical methods and learning\Supervised learning Statistical methods and learning\Unsupervised learning |
| • Peter Gehler University of Tubingen, Germany |
Secondary Subject Area(s): Optimization methods\Inference in graphical models Recognition: detection, categorization, indexing, matching\3D representations for recognition Recognition: detection, categorization, indexing, matching\Human pose estimation Recognition: detection, categorization, indexing, matching\Instance detection and recognition Segmentation, grouping and shape representation\Semantic image segmentation |
| • Zhuowen Tu UCSD, USA |
Secondary Subject Area(s): Biomedical image analysis Low-level vision and image processing\Edge and contour detection Recognition: detection, categorization, indexing, matching\Context Recognition: detection, categorization, indexing, matching\Object class detection and recognition Segmentation, grouping and shape representation |
Primary Subject Area: Statistical methods and learning\Deep learning and convolutional neural networks | |
| • Honglak Lee University of Michigan, USA |
Secondary Subject Area(s): Statistical methods and learning |
| • Marc'Aurelio Ranzato Facebook AI Research, Menlo Park, USA |
Secondary Subject Area(s): Low-level vision and image processing\Biologically-inspired vision Optimization methods\Sparse coding and dictionaries Recognition: detection, categorization, indexing, matching\Images and language Recognition: detection, categorization, indexing, matching\Large scale visual recognition Statistical methods and learning\Unsupervised learning |
| • Trevor Darrell UC Berkeley, USA |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching Statistical methods and learning |
| • Xiaogang Wang The Chinese University of Hong Kong, HK |
Secondary Subject Area(s): Face and gesture\Face recognition Face and gesture\Human identification Recognition: detection, categorization, indexing, matching\Human pose estimation Recognition: detection, categorization, indexing, matching\Object class detection and recognition Video: events, activities and surveillance |
Primary Subject Area: Video: events, activities and surveillance | |
| • Antoni Chan City University of Hong Kong, Hong Kong |
Secondary Subject Area(s): Motion and tracking\People tracking Statistical methods and learning\Bayesian modeling Statistical methods and learning\Kernel methods Statistical methods and learning\Supervised learning Statistical methods and learning\Unsupervised learning |
| • Cordelia Schmid INRIA Grenoble, France |
Secondary Subject Area(s): Motion and tracking\Object tracking and motion analysis Motion and tracking\Optical flow Recognition: detection, categorization, indexing, matching Segmentation, grouping and shape representation\Semantic image segmentation Statistical methods and learning |
| • Gianfranco Doretto West Virginia University, USA |
Secondary Subject Area(s): Face and gesture Low-level vision and image processing\Texture analysis and synthesisContext Motion and tracking Recognition: detection, categorization, indexing, matching Statistical methods and learning |
| • Greg Mori Simon Fraser University, Canada |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Context Recognition: detection, categorization, indexing, matching\Human pose estimation Recognition: detection, categorization, indexing, matching\Scene understanding |
| • Jason Corso University of Michigan, USA |
|
| • Larry Davis University of Maryland, USA |
Secondary Subject Area(s): Face and gesture\Biometrics Recognition: detection, categorization, indexing, matching\Attributes Recognition: detection, categorization, indexing, matching\Context |
| • Rahul Sukthankar Google Research, Mountain View, USA |
Secondary Subject Area(s): Low-level vision and image processing\Feature extraction and matching Recognition: detection, categorization, indexing, matching\Image indexing and retrieval Recognition: detection, categorization, indexing, matching\Large scale visual recognition Statistical methods and learning\Deep learning and convolutional neural networks Statistical methods and learning\Transfer learning |
Primary Subject Area: Video: events, activities and surveillance\Events, actions and activity recognition | |
| • Alvaro Soto Catholic University of Chile, Chile |
Secondary Subject Area(s): Optimization methods\Sparse coding and dictionaries Recognition: detection, categorization, indexing, matching\Large scale visual recognition Recognition: detection, categorization, indexing, matching\Object class detection and recognition Statistical methods and learning\Large scale learning methods |
| • Juan Carlos Niebles Universidad del Norte, Colombia |
Secondary Subject Area(s): |
Primary Subject Area: Video: events, activities and surveillance\Video indexing and retrieval | |
| • Shin'ichi Satoh National Institute of Informatics, Japan |
Secondary Subject Area(s): Recognition: detection, categorization, indexing, matching\Image indexing and retrieval |
Primary Subject Area: Video: events, activities and surveillance\Video surveillance | |
| • Gerard Medioni University of Southern California, USA |
Secondary Subject Area(s): 3D computer vision\3D modeling and reconstruction Face and gesture\Face recognition Motion and tracking\Object tracking and motion analysis Recognition: detection, categorization, indexing, matching\3D representations for recognition Segmentation, grouping and shape representation\Grouping |