| Memory replay gans: Learning to generate new categories without forgetting C Wu, L Herranz, X Liu, J van de Weijer, B Raducanu Advances in Neural Information Processing Systems 31, 5962-5972, 2018 | 174* | 2018 |
| Scene recognition with cnns: objects, scales and dataset bias L Herranz, S Jiang, X Li Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 153 | 2016 |
| Rotate your networks: Better weight consolidation and less catastrophic forgetting X Liu, M Masana, L Herranz, J Van de Weijer, AM Lopez, AD Bagdanov 2018 24th International Conference on Pattern Recognition (ICPR), 2262-2268, 2018 | 109 | 2018 |
| Transferring gans: generating images from limited data Y Wang, C Wu, L Herranz, J van de Weijer, A Gonzalez-Garcia, ... Proceedings of the European Conference on Computer Vision (ECCV), 218-234, 2018 | 96 | 2018 |
| LIUM-CVC submissions for WMT17 multimodal translation task O Caglayan, W Aransa, A Bardet, M García-Martínez, F Bougares, ... arXiv preprint arXiv:1707.04481, 2017 | 80 | 2017 |
| Geolocalized modeling for dish recognition R Xu, L Herranz, S Jiang, S Wang, X Song, R Jain IEEE transactions on multimedia 17 (8), 1187-1199, 2015 | 77 | 2015 |
| Being a supercook: Joint food attributes and multimodal content modeling for recipe retrieval and exploration W Min, S Jiang, J Sang, H Wang, X Liu, L Herranz IEEE Transactions on Multimedia 19 (5), 1100-1113, 2016 | 69 | 2016 |
| Depth CNNs for RGB-D scene recognition: Learning from scratch better than transferring from RGB-CNNs X Song, L Herranz, S Jiang Thirty-first AAAI conference on artificial intelligence, 2017 | 60 | 2017 |
| Multi-scale multi-feature context modeling for scene recognition in the semantic manifold X Song, S Jiang, L Herranz IEEE Transactions on Image Processing 26 (6), 2721-2735, 2017 | 47 | 2017 |
| Domain-adaptive deep network compression M Masana, J van de Weijer, L Herranz, AD Bagdanov, JM Alvarez Proceedings of the IEEE International Conference on Computer Vision, 4289-4297, 2017 | 45 | 2017 |
| Semantic drift compensation for class-incremental learning L Yu, B Twardowski, X Liu, L Herranz, K Wang, Y Cheng, S Jui, J Weijer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 44 | 2020 |
| Modeling restaurant context for food recognition L Herranz, S Jiang, R Xu IEEE Transactions on Multimedia 19 (2), 430-440, 2016 | 42 | 2016 |
| Minegan: effective knowledge transfer from gans to target domains with few images Y Wang, A Gonzalez-Garcia, D Berga, L Herranz, FS Khan, J Weijer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 33 | 2020 |
| Generative feature replay for class-incremental learning X Liu, C Wu, M Menta, L Herranz, B Raducanu, AD Bagdanov, S Jui, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 32 | 2020 |
| Joint multi-feature spatial context for scene recognition on the semantic manifold X Song, S Jiang, L Herranz Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 32 | 2015 |
| A framework for scalable summarization of video L Herranz, JM Martinez IEEE Transactions on Circuits and Systems for Video Technology 20 (9), 1265-1270, 2010 | 30 | 2010 |
| Mix and match networks: encoder-decoder alignment for zero-pair image translation Y Wang, J van de Weijer, L Herranz Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 29 | 2018 |
| Introducing CAIN: A metadata-driven content adaptation manager integrating heterogeneous content adaptation tools JM Martínez, V Valdés, J Bescós, L Herranz Proceedings of the WIAMIS, 2005 | 28 | 2005 |
| Learning effective RGB-D representations for scene recognition X Song, S Jiang, L Herranz, C Chen IEEE Transactions on Image Processing 28 (2), 980-993, 2018 | 25 | 2018 |
| Combining Models from Multiple Sources for RGB-D Scene Recognition. X Song, S Jiang, L Herranz IJCAI, 4523-4529, 2017 | 21 | 2017 |
Shuqiang JiangInstitute of Computing Technology, Chinese Academy of SciencesVerifierad e-postadress på ict.ac.cn
