Gemma Roig

Projects

Invariance and Selectivity in Representation Learning

CBMM Publications

Y. Han, Roig, G., Geiger, G., and Poggio, T., “Scale and translation-invariance for novel objects in human vision”, Scientific Reports, vol. 10, no. 1411, 2020.
J. Zhang, Han, Y., Poggio, T., and Roig, G., “Eccentricity Dependent Neural Network with Recurrent Attention for Scale, Translation and Clutter Invariance ”, in Vision Science Society, Florida, USA, 2019.
Y. Han, Roig, G., Geiger, G., and Poggio, T., “Properties of invariant object recognition in human one-shot learning suggests a hierarchical architecture different from deep convolutional neural networks”, in Vision Science Society, Florida, USA, 2019.
Y. Han, Roig, G., Geiger, G., and Poggio, T., “Properties of invariant object recognition in human oneshot learning suggests a hierarchical architecture different from deep convolutional neural networks ”, in Vision Science Society, St Pete Beach, FL, USA, 2019.
F. Chen, Roig, G., Isik, L., Boix, X., and Poggio, T., “Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision”, in AAAI Spring Symposium Series, Science of Intelligence, 2017.
Y. Han, Roig, G., Geiger, G., and Poggio, T., “Is the Human Visual System Invariant to Translation and Scale?”, in AAAI Spring Symposium Series, Science of Intelligence, 2017.
G. Roig, Chen, F., Boix, X., and Poggio, T., “Eccentricity Dependent Deep Neural Networks for Modeling Human Vision”, Vision Sciences Society. 2017.
Y. Han, Roig, G., Geiger, G., and Poggio, T., “On the Human Visual System Invariance to Translation and Scale”, Vision Sciences Society. 2017.
A. Volokitin and Roig, G., “Do Deep Neural Networks Suffer from Crowding? [code]”. 2017.
A. Volokitin, Roig, G., and Poggio, T., “Do Deep Neural Networks Suffer from Crowding?”. 2017.
Y. Luo, Boix, X., Roig, G., Poggio, T., and Zhao, Q., “Foveation-based Mechanisms Alleviate Adversarial Examples”. 2016.