Gemma Roig

Ass. Prof. at  SUTD

Research Affiliate at MIT

Computational Vision  and Artificial Intelligence

Note: I am looking for students to work on a project related to Computational Human Vision and Deep Learning. If you are interested, please send me and email to gemmar@mit.edu.

Bio

My research aim is to build computational models of human vision to understand its underlying principles, and to use those models to build applications of artificial intelligence.

 

I am currently an assistant professor at Singapore University of Technology and Design. I am also a research affiliate at MIT. Previously, I was a postdoctoral fellow at MIT in the Center for Brains Minds and Machines, with  Prof. Tomaso Poggio as my faculty host. I was also affiliated at the Laboratory for Computational and Statistical Learning, which is a collaborative agreement between the Istituto Italiano di Tecnologia and the Massachusetts Institute of Technology.  I pursued my doctoral degree in Computer Vision at ETH Zurich. Previously, I was a research assistant at the Computer Vision Lab at EPFL in Lausanne, at the Department of Media Technologies at Ramon Llull University in Barcelona, and at the Robotics Institute - Carnegie Mellon University in Pittsburgh.

Publications

Google scholar profile

 

 

  • Do Deep Neural Networks Suffer from Crowding?
  • A. Volokitin, G. Roig, T. Poggio
  • In Proc. of Neural Information Processing Systems (NIPS), 2017
  • [pdf][bib][code]

 

  • Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision
  • F. Chen, G. Roig, L. Isik, X. Boix and T. Poggio
  • In AAAI Spring Symposium Series, Science of Intelligence, 2017
  • [pdf][bib]

 

  • Is the Human Visual System Invariant to Translation and Scale?
  • Y. Han, G. Roig, G. Geiger and T. Poggio
  • In AAAI Spring Symposium Series, Science of Intelligence, 2017
  • [pdf][bib]

 

  • Herding Generalizes Diverse M-Best Solutions

        E. Ozcan, G. Roig, O. Goksel, X. Boix

        In arxiv:1611.04353, 2016

        [pdf][bib]

 

  • Learning to Predict Sequences of Human Visual Fixations
  • M. Jiang, X. Boix, G. Roig, J. Xu, L. Van Gool, and Q. Zhao
  • In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2016
  • [pdf][bib]

 

  • Foveation-based Mechanisms Alleviate Adversarial Examples
  • Y. Luo, X. Boix, G. Roig, T. Poggio, Q. Zhao
  • CBMM memo 044, arXiv:1511.06292, 2015
  • [pdf][bib]

 

  • SEEDS: Superpixels Extracted via Energy-Driven Sampling

 

  • Saliency Prediction with Active Semantic Segmentation
  • M. Jiang, X. Boix, J. Xu, G. Roig, L. Van Gool, Q. Zhao
  • In Proc. of British Machine Vision Conference (BMVC), 2015
  • [pdf][bib]

 

  • Self-Adaptable Templates for Feature Coding
  • X. Boix*, G. Roig*, Salomon Diether, L. Van Gool
  • In Proc. of Neural Information Processing Systems (NIPS), 2014
  • (*equal contribution). [pdf][bib]

 

  • Random Binary Mappings for Kernel Learning and Efficient SVM
  • G. Roig*, X. Boix*, L. Van Gool
  • In arXiv:1307.5161, 2014
  • (*equal contribution). [pdf][bib]
  •  
  • Comment on "Ensemble Projection for Semi-supervised Image Classification"
  • X. Boix, G. Roig, L. Van Gool
  • In  arXiv:1408.6963, 2014
  • [pdf][bib]

 

  • Active MAP Inference in CRFs for Efficient Semantic Segmentation
  • G. Roig*, X. Boix*, R. de Nijs, S. Ramos, K. Kuehnlenz, L. Van Gool
  • In Proc. of International Conferenence on Computer Vision (ICCV), 2013
  • (Oral, *equal contribution). [pdf][bib]

 

  • Online Video SEEDS for Temporal Window Objectness
  • M. Van den Bergh, G. Roig, X. Boix, S. Manen, L. Van Gool
  • In Proc. of International Conferenence on Computer Vision (ICCV), 2013
  •  [pdf][bib][code][project]

 

  • Sparse Quantization for Patch Description
  • X. Boix, M. Gygli, G. Roig, L. Van Gool
  • In Proc. of Computer Vision and Pattern Recognition (CVPR), 2013
  • [pdf][bib]

 

  • Nested Sparse Quantization for Efficient Feature Coding
  • X. Boix*, G. Roig*, L. Van Gool
  • In Proc. of European Conferenence on Computer Vision (ECCV), 2012
  • (*equal contribution). [pdf][bib]

 

  • SEEDS: Superpixels Extracted via Energy-Driven Sampling

 

  • On-line Semantic Perception Using Uncertainty
  • R. de Nijs, S. Ramos, G. Roig, X. Boix, L. Van Gool, K. Kühnlenz
  • In Proc. of International Conference on Intelligent Robots and Systems (IROS), 2012
  • [pdf][bib]

 

  • Robotic ADaptation to Humans Adapting to Robots: Overview of the FP7 project RADHAR.
  • E. Demeester, E. Vander Poorten, A. Hüntemann, J. De Schutter, B. Lau, M. Kuderer, W. Burgard, A. Fossati, G. Roig, X. Boix, M. Ristin, L. Van Gool, et al..
  • In Proc. of 1st International Conference on Systems and Computer Science, 2012
  • [pdf][bib][project]

 

  • Conditional Random Fields for Multi-Camera Object Detection.
  • G. Roig*, X. Boix*, H. Ben Shitrit, P. Fua.
  • In Proc. of International Conferenence on Computer Vision (ICCV), 2011.
  • (*equal contribution). [pdf][bib][project]

 

  • Hierarchical CRF with Product Label Spaces for Parts-based Models.
  • G. Roig*, X. Boix*, F. De la Torre, J. Serrat, C. Vilella.
  • In Proc. of Face and Gesture (FG) 2011.
  • (Oral, *equal contribution). [pdf][bib]

 

  • Optimal Feature Selection for Subspace Image Matching.
  • G. Roig, X. Boix, F. De la Torre.
  • In Proc. of International Conference on Computer Vision Workshops (ICCVW), 2009.
  • [pdf][bib]

 

 

 

       INTERNATIONAL WORKSHOPS AND CONFERENCE ABSTRACTS

 

  • Eccentricity Dependent Deep Neural Networks for Modeling Human Vision.

        G. Roig, F. Chen, X. Boix and T. Poggio.

        Vision Sciences Society, 2017.

       (Abstract + poster).

 

  • On the Human Visual System Invariance to Translation and Scale.
  • Y. Han, G. Roig, G. Gaiger and T. Poggio.
  • Vision Sciences Society, 2017.

        (Abstract + poster).

 

  • Online Video SEEDS for Temporal Window Objectness.
  • M. Van den Bergh, G. Roig, X. Boix, S. Manen, L. Van Gool.
  • In European Conferenence on Computer Vision (ECCVW), 2013.
  • (Talk + poster).

 

  • Ensemble Kernel Learning.
  • G. Roig*, X. Boix*, C. Leistner, L. Van Gool.
  • In International Conferenence on Computer Vision Workshops (ICCVW), 2011.
  • (Abstract + poster).

 

 

Contact

Gemma Roig, PhD

 

gemmar@mit.edu

 

Singapore University of Technology and Design

Information Systems Technology and Design Pillar

8 Somapah Road,

Building 1, level 7

Singapore 487372



 

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