WILLOW Research team
Models of visual object recognition and scene understanding
- Leader : Jean Ponce
- Type : Project team
- Research center(s) : Paris
- Field : Perception, Cognition and Interaction
- Theme : Vision, perception and multimedia interpretation
- Partner(s) : Ecole normale supérieure de Paris,CNRS
- Collaborator(s) : Département d'Informatique de l'Ecole Normale Supérieure (UMR8548)
Our research is concerned with representational issues in visual object recognition and scene understanding. Our objective is to develop geometric, physical, and statistical models for all components of the image interpretation process, including illumination, materials, objects, scenes, and human activities. These models will be used to tackle fundamental scientific challenges such as three-dimensional (3D) object and scene modeling, analysis, and retrieval; human activity capture and classification; and category-level object and scene recognition. They will also support applications with high scientific, societal, and/or economic impact in domains such as quantitative image analysis in domains such as archaeology and cultural heritage conservation; film post-production and special effects; and video annotation, interpretation, and retrieval.
We follow three main research directions:
- 3D object and scene modeling, analysis, and retrieval:
This part of our research addresses the problem of acquiring high-accuracy geometric models of complex 3D objects from multiple images, and using these models in rigid and nonrigid registration and retrieval tasks.
- Human activity capture and classification:
This includes combining object detection and tracking to associate multiple ocurrences of faces and bodies in video footage, and constructing and recognizing spatio-temporal models of human activities and interactions.
- Category-level object and scene recognition:
This part of our research is concerned with developing geometric and statistical models of objects, scenes, and their components that support semi-supervised learning, effectively handle image variability, and efficiently support inference.
International and industrial relations
WILLOW is part of the THETYS associated team, in collaboration with the LEAR project-team of INRIA Grenoble - Rhône-Alpes research centre, Carnegie Mellon University, and the University of Illinois at Urbana-Champaign.
WILLOW members also collaborate with researchers at Caltech, FT R&D, ILM, Microsoft, MIT, MYU, and Toyota.
Research teams of the same theme :
- LINKMEDIA - Creating and exploiting explicit links between multimedia fragments
- MAGRIT - Visual Augmentation of Complex Environments
- MORPHEO - Capture and Analysis of Shapes in Motion
- PERCEPTION - Interpretation and Modelling of Images and Videos
- SIROCCO - Analysis representation, compression and communication of visual data
- STARS - Spatio-Temporal Activity Recognition Systems
- THOTH - Learning visual models from large-scale data