| Understanding deep image representations by inverting them A Mahendran, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 1968 | 2015 |
| Visualizing deep convolutional neural networks using natural pre-images A Mahendran, A Vedaldi International Journal of Computer Vision 120, 233-255, 2016 | 515 | 2016 |
| Object-centric learning with slot attention F Locatello, D Weissenborn, T Unterthiner, A Mahendran, G Heigold, ... Advances in Neural Information Processing Systems 33, 11525-11538, 2020 | 366 | 2020 |
| Salient deconvolutional networks A Mahendran, A Vedaldi Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 121 | 2016 |
| Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 73 | 2021 |
| Cross pixel optical-flow similarity for self-supervised learning A Mahendran, J Thewlis, A Vedaldi Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 64 | 2019 |
| Self-supervised learning of video-induced visual invariances M Tschannen, J Djolonga, M Ritter, A Mahendran, N Houlsby, S Gelly, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 52 | 2020 |
| Differentiable patch selection for image recognition JB Cordonnier, A Mahendran, A Dosovitskiy, D Weissenborn, J Uszkoreit, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 48 | 2021 |
| Simple open-vocabulary object detection with vision transformers M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... arXiv preprint arXiv:2205.06230, 2022 | 37 | 2022 |
| Heterogeneous UGV-MAV exploration using integer programming A Dewan, A Mahendran, N Soni, KM Krishna Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International …, 2013 | 30 | 2013 |
| Savi++: Towards end-to-end object-centric learning from real-world videos G Elsayed, A Mahendran, S van Steenkiste, K Greff, MC Mozer, T Kipf Advances in Neural Information Processing Systems 35, 28940-28954, 2022 | 20 | 2022 |
| Object scene representation transformer MSM Sajjadi, D Duckworth, A Mahendran, S van Steenkiste, F Pavetic, ... Advances in Neural Information Processing Systems 35, 9512-9524, 2022 | 17 | 2022 |
| Researchdoom and cocodoom: Learning computer vision with games A Mahendran, H Bilen, JF Henriques, A Vedaldi arXiv preprint arXiv:1610.02431, 2016 | 17 | 2016 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... arXiv preprint arXiv:2302.05442, 2023 | 11 | 2023 |
| Self-supervised segmentation by grouping optical-flow A Mahendran, J Thewlis, A Vedaldi Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 10 | 2018 |
| Representation learning from videos in-the-wild: An object-centric approach R Romijnders, A Mahendran, M Tschannen, J Djolonga, M Ritter, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 7 | 2021 |
| UGV-MAV collaboration for augmented 2D maps A Mahendran, A Dewan, N Soni, KM Krishna Proceedings of Conference on Advances In Robotics, 1-6, 2013 | 7 | 2013 |
| Bus detection for adaptive traffic signal control A Mahendran, M Hebert, S Smith, XF Xie Carnegie-Mellon University, 2014 | 6 | 2014 |
| Optimization Based coordinated uGV-MAV exploration for 2D augmented mapping A Dewan, A Mahendran, N Soni, KM Krishna Proceedings of the 2013 international conference on Autonomous agents and …, 2013 | 3 | 2013 |
| Self-supervised learning using motion and visualizing convolutional neural networks A Mahendran University of Oxford, 2018 | 1 | 2018 |
Andrea VedaldiUniversity of OxfordVerified email at robots.ox.ac.uk
