| Seeds: Superpixels extracted via energy-driven sampling M Van den Bergh, X Boix, G Roig, B de Capitani, L Van Gool European conference on computer vision, 13-26, 2012 | 508 | 2012 |
| Seeds: Superpixels extracted via energy-driven sampling M Van den Bergh, X Boix, G Roig, L Van Gool International Journal of Computer Vision 111 (3), 298-314, 2015 | 289 | 2015 |
| JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields QH Pham, DT Nguyen, BS Hua, G Roig, SK Yeung 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019 | 223 | 2019 |
| Foveation-based mechanisms alleviate adversarial examples Y Luo, X Boix, G Roig, T Poggio, Q Zhao arXiv preprint arXiv:1511.06292, 2015 | 199 | 2015 |
| Doping: Generative data augmentation for unsupervised anomaly detection with gan SK Lim, Y Loo, NT Tran, NM Cheung, G Roig, Y Elovici 2018 IEEE international conference on data mining (ICDM), 1122-1127, 2018 | 145 | 2018 |
| Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning K Dwivedi, G Roig 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019 | 124 | 2019 |
| 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 | 105 | 2013 |
| 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 | 64 | 2016 |
| Z-Inspection®: A Process to Assess Trustworthy AI RV Zicari, J Brodersen, J Brusseau, B Düdder, T Eichhorn, T Ivanov, ... IEEE Transactions on Technology and Society 2 (2), 83-97, 2021 | 63 | 2021 |
| 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 | 57 | 2011 |
| Scale and translation-invariance for novel objects in human vision Y Han, G Roig, G Geiger, T Poggio Scientific Reports 10, 2020 | 49 | 2020 |
| LCD: Learned Cross-Domain Descriptors for 2D-3D Matching QH Pham, MA Uy, BS Hua, DT Nguyen, G Roig, SK Yeung In Proc. of the AAAI Conference on Artificial Intelligence, 2020 | 49 | 2020 |
| The algonauts project: A platform for communication between the sciences of biological and artificial intelligence RM Cichy, G Roig, A Andonian, K Dwivedi, B Lahner, A Lascelles, ... arXiv preprint arXiv:1905.05675, 2019 | 41 | 2019 |
| 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 |
| Do Deep Neural Networks Suffer from Crowding? A Volokitin, G Roig, TA Poggio Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017 | 32 | 2017 |
| Unveiling functions of the visual cortex using task-specific deep neural networks K Dwivedi, MF Bonner, RM Cichy, G Roig PLoS computational biology 17 (8), e1009267, 2021 | 28* | 2021 |
| Regression-based music emotion prediction using triplet neural networks KW Cheuk, YJ Luo, B BT, G Roig, D Herremans International Joint Conference on Neural Networks (IJCNN), 2020 | 26 | 2020 |
| Nested sparse quantization for efficient feature coding X Boix, G Roig, C Leistner, L Van Gool Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 26 | 2012 |
| Multi-Source Open-Set Deep Adversarial Domain Adaptation S Rakshit, D Tamboli, PS Meshram, B Banerjee, G Roig, S Chaudhuri European Conferenence on Computer Vision (ECCV), 2020 | 25 | 2020 |
| Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision FX Chen, G Roig, L Isik, X Boix, T Poggio 2017 AAAI Spring Symposium Series, Science of Intelligence: Computational …, 2017 | 25 | 2017 |
