| Understanding deep image representations by inverting them A Mahendran, A Vedaldi Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 2352 | 2015 |
| 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 | 759 | 2020 |
| Visualizing deep convolutional neural networks using natural pre-images A Mahendran, A Vedaldi International Journal of Computer Vision 120, 233-255, 2016 | 629 | 2016 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning, 7480-7512, 2023 | 397 | 2023 |
| Simple open-vocabulary object detection M Minderer, A Gritsenko, A Stone, M Neumann, D Weissenborn, ... European Conference on Computer Vision, 728-755, 2022 | 388 | 2022 |
| Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 186 | 2021 |
| Salient deconvolutional networks A Mahendran, A Vedaldi Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 149 | 2016 |
| 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 | 116 | 2022 |
| 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 | 96 | 2021 |
| 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 | 92 | 2022 |
| 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 | 81 | 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 | 75 | 2020 |
| 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 | 31 | 2013 |
| Invariant slot attention: Object discovery with slot-centric reference frames O Biza, S Van Steenkiste, MSM Sajjadi, GF Elsayed, A Mahendran, T Kipf arXiv preprint arXiv:2302.04973, 2023 | 20 | 2023 |
| Rust: Latent neural scene representations from unposed imagery MSM Sajjadi, A Mahendran, T Kipf, E Pot, D Duckworth, M Lučić, K Greff Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 20 | 2023 |
| Researchdoom and cocodoom: Learning computer vision with games A Mahendran, H Bilen, JF Henriques, A Vedaldi arXiv preprint arXiv:1610.02431, 2016 | 19 | 2016 |
| 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 | 15 | 2018 |
| Iterative patch selection for high-resolution image recognition B Bergner, C Lippert, A Mahendran arXiv preprint arXiv:2210.13007, 2022 | 9 | 2022 |
| 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 | 9 | 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 | 9 | 2013 |
Thomas KipfStaff Research Scientist, Google DeepMindVerified email at google.com
