- machine learning
- deep learning
- computer vision
- data analytics
- artificial intelligence
I am a senior research scientist in the Computer Vision group. My research focuses on applying machine learning to several computer vision tasks. I am particulary interested in getting a semantic and global understanding of visual scenes. I have recently worked on instance-level and semantic visual search. I am also interested in representing the structure and geometry of object categories, and in reasoning at the scene-level with images and text.
- 1 paper accepted at ICCV 17 (oral presentation)
- CVPR 17 best reviewer award
- 2 papers accepted at CVPR17:
- AnchorNet: a weakly supervised network to learn geometry-sensitive features for semantic matching.
- Beyond instance-level image retrieval: Leveraging human captions to learn representations for semantic visual search.
- ECCV 16 best reviewer award
- 1 paper accepted at ECCV16: Deep Image Retrieval: Learning global representations for image search.
Publications since I joined the center are available here: Publications
Current and past collaborations
Andrew Zisserman and Andrea Vedaldi, from the University of Oxford, around object recognition (UAC, 2011-2014), .
I am now jointly supervising David Novotny (since 2015) with Andrea Vedaldi.
- Svetlana Lazebnik, from the University of Illinois at Urbana-Champaign (UAC, 2013-2016)
- Sabine Süsstrunk, from EPFL, around scene understanding using visible and near-infrared data (UAC, then Open Innovation project, 2010 to 2013)
I obtained a M.Sc. in Image, Vision and Robotics from UJF/INP, Grenoble, France, in 2005. From 2005 to 2008, I worked as a doctoral candidate in the LEAR group, at INRIA Grenoble. During the summer 2007, I did an internship at the JRL/AIST laboratory in Tsukuba, Japan. I obtained my Ph.D. in 2008, from INP Grenoble. From 2008 to 2010, I worked as a post-doc at TU Darmstadt, Germany. I joined what has now become NAVER LABS Europe in 2010.