| 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 | 852 | 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 | 248 | 2019 |
| Foveation-based mechanisms alleviate adversarial examples Y Luo, X Boix, G Roig, T Poggio, Q Zhao arXiv preprint arXiv:1511.06292, 2015 | 217 | 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 | 170 | 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 | 157 | 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 | 107 | 2013 |
| 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 | 97 | 2021 |
| 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 | 72 | 2016 |
| 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 | 70 | 2020 |
| Scale and translation-invariance for novel objects in human vision Y Han, G Roig, G Geiger, T Poggio Scientific Reports 10, 2020 | 66 | 2020 |
| 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 | 62 | 2011 |
| A large and rich EEG dataset for modeling human visual object recognition AT Gifford, K Dwivedi, G Roig, RM Cichy NeuroImage 264, 119754, 2022 | 61 | 2022 |
| 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 | 45 | 2019 |
| 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 | 40 | 2021 |
| 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 | 39 | 2020 |
| Do Deep Neural Networks Suffer from Crowding? A Volokitin, G Roig, TA Poggio Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017 | 38 | 2017 |
| 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 | 37 | 2013 |
| 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 | 32 | 2020 |
| Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning K Dwivedi, J Huang, RM Cichy, G Roig European Conference on Computer Vision (ECCV), 2020 | 31 | 2020 |
| Unsupervised multi-source domain adaptation driven by deep adversarial ensemble learning S Rakshit, B Banerjee, G Roig, S Chaudhuri Pattern Recognition: 41st DAGM German Conference, DAGM GCPR 2019, Dortmund …, 2019 | 30 | 2019 |
