| Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks X Huang, C Shen, X Boix, Q Zhao Proceedings of the IEEE international conference on computer vision, 262-270, 2015 | 720 | 2015 |
| Seeds: Superpixels extracted via energy-driven sampling MV Bergh, X Boix, G Roig, B Capitani, LV Gool European conference on computer vision, 13-26, 2012 | 570 | 2012 |
| SEEDS: Superpixels Extracted via Energy-Driven Sampling M Van den Bergh, X Boix, G Roig, L Van Gool International journal computer vision 111 (3), 298-314, 2015 | 333 | 2015 |
| Foveation-based mechanisms alleviate adversarial examples Y Luo, X Boix, G Roig, T Poggio, Q Zhao arXiv preprint arXiv:1511.06292, 2015 | 214 | 2015 |
| Harmony potentials for joint classification and segmentation JM Gonfaus, X Boix, J Van de Weijer, AD Bagdanov, J Serrat, J Gonzalez 2010 IEEE computer society conference on computer vision and pattern …, 2010 | 204 | 2010 |
| Theory of deep learning III: explaining the non-overfitting puzzle T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ... arXiv preprint arXiv:1801.00173, 2017 | 138 | 2017 |
| Harmony potentials X Boix, JM Gonfaus, J Van De Weijer, AD Bagdanov, J Serrat, J Gonzalez International journal of computer vision 96 (1), 83-102, 2012 | 118 | 2012 |
| Online video seeds for temporal window objectness M Van den Bergh, G Roig, X Boix, S Manen, L Van Gool Proceedings of the IEEE international conference on computer vision, 377-384, 2013 | 106 | 2013 |
| Are spatial and global constraints really necessary for segmentation? A Lucchi, Y Li, X Boix, K Smith, P Fua 2011 international conference on computer vision, 9-16, 2011 | 87 | 2011 |
| Learning to predict sequences of human visual fixations M Jiang, X Boix, G Roig, J Xu, L Van Gool, Q Zhao IEEE transactions on neural networks and learning systems 27 (6), 1241-1252, 2016 | 74 | 2016 |
| The Language of Fake News: Opening the Black-Box of Deep Learning Based Detectors N O'Brien, S Latessa, G Evangelopoulos, X Boix NIPS Workshop on AI for Social Good, 2018 | 66 | 2018 |
| Conditional random fields for multi-camera object detection G Roig, X Boix, HB Shitrit, P Fua 2011 International Conference on Computer Vision, 563-570, 2011 | 66 | 2011 |
| Active Video Summarization: Customized Summaries via On-line Interaction A Garcia del Molino, X Boix, J Lim, A Tan AAAI Conference on Artificial Intelligence, 2017 | 38 | 2017 |
| When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations S Madan, T Henry, J Dozier, H Ho, N Bhandari, T Sasaki, F Durand, ... Nature Machine Intelligence 4 (2), 146-153, 2022 | 37 | 2022 |
| Active map inference in crfs for efficient semantic segmentation G Roig, X Boix, R De Nijs, S Ramos, K Kuhnlenz, L Van Gool Proceedings of the IEEE International Conference on Computer Vision, 2312-2319, 2013 | 36 | 2013 |
| Theory IIIb: Generalization in deep networks T Poggio, Q Liao, B Miranda, A Banburski, X Boix, J Hidary arXiv preprint arXiv:1806.11379, 2018 | 33 | 2018 |
| Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images S Srivastava, G Ben-Yosef, X Boix ICLR 2019, 2019 | 31 | 2019 |
| Theory of deep learning iii: the non-overfitting puzzle T Poggio, K Kawaguchi, Q Liao, B Miranda, L Rosasco, X Boix, J Hidary, ... CBMM Memo. 073, 2018 | 29 | 2018 |
| Frivolous Units: Wider Networks Are Not Really That Wide S Casper, X Boix, V D'Amario, L Guo, M Schrimpf, K Vinken, G Kreiman AAAI, 2021 | 28 | 2021 |
| Eccentricity dependent deep neural networks: Modeling invariance in human vision. FX Chen, G Roig, L Isik, X Boix, TA Poggio AAAI Spring Symposia, 2017 | 26 | 2017 |