| Higher order conditional random fields in deep neural networks A Arnab, S Jayasumana, S Zheng, PHS Torr European Conference on Computer Vision, 524-540, 2016 | 228* | 2016 |
| Pixelwise instance segmentation with a dynamically instantiated network A Arnab, PHS Torr Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 171 | 2017 |
| On the robustness of semantic segmentation models to adversarial attacks A Arnab, O Miksik, PHS Torr IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 888-897, 2018 | 122 | 2018 |
| Weakly-and Semi-Supervised Panoptic Segmentation Q Li, A Arnab, PHS Torr Proceedings of the European Conference on Computer Vision (ECCV), 102-118, 2018 | 86 | 2018 |
| Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ... IEEE Signal Processing Magazine 35 (1), 37-52, 2018 | 75 | 2018 |
| Exploiting temporal context for 3D human pose estimation in the wild A Arnab, C Doersch, A Zisserman Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 64 | 2019 |
| Bottom-up instance segmentation using deep higher-order crfs A Arnab, PHS Torr Proceedings of the British Machine Vision Conference (BMVC), 2016 | 49 | 2016 |
| Dual graph convolutional network for semantic segmentation L Zhang, X Li, A Arnab, K Yang, Y Tong, PHS Torr arXiv preprint arXiv:1909.06121, 2019 | 35 | 2019 |
| Holistic, Instance-Level Human Parsing Q Li, A Arnab, PHS Torr Proceedings of the British Machine Vision Conference (BMVC), 2017 | 29 | 2017 |
| A projected gradient descent method for CRF inference allowing end-to-end training of arbitrary pairwise potentials M Larsson, A Arnab, F Kahl, S Zheng, P Torr International Conference on Energy Minimization Methods in Computer Vision …, 2017 | 22* | 2017 |
| Dynamic graph message passing networks L Zhang, D Xu, A Arnab, PHS Torr Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 19 | 2020 |
| Semanticpaint: interactive segmentation and learning of 3d worlds S Golodetz, M Sapienza, JPC Valentin, V Vineet, MM Cheng, ... ACM SIGGRAPH 2015 Emerging Technologies, 1-1, 2015 | 13 | 2015 |
| Meta learning deep visual words for fast video object segmentation HS Behl, M Najafi, A Arnab, PHS Torr arXiv preprint arXiv:1812.01397, 2018 | 12 | 2018 |
| Semanticpaint: A framework for the interactive segmentation of 3d scenes S Golodetz, M Sapienza, JPC Valentin, V Vineet, MM Cheng, A Arnab, ... arXiv preprint arXiv:1510.03727, 2015 | 12 | 2015 |
| Deep fully-connected part-based models for human pose estimation R de Bem, A Arnab, S Golodetz, M Sapienza, P Torr Asian Conference on Machine Learning, 327-342, 2018 | 10 | 2018 |
| Joint object-material category segmentation from audio-visual cues A Arnab, M Sapienza, S Golodetz, J Valentin, O Miksik, S Izadi, P Torr Proceedings of the British Machine Vision Conference (BMVC), 2015 | 10 | 2015 |
| Revisiting deep structured models for pixel-level labeling with gradient-based inference M Larsson, A Arnab, S Zheng, P Torr, F Kahl SIAM Journal on Imaging Sciences 11 (4), 2610-2628, 2018 | 5 | 2018 |
| 2020 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 42 A Aberdam, J Achterhold, JK Adams, E Adeli, S Agaian, K Aizawa, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (1), 2021 | | 2021 |
| Uncertainty-Aware Weakly Supervised Action Detection from Untrimmed Videos A Arnab, C Sun, A Nagrani, C Schmid European Conference on Computer Vision, 751-768, 2020 | | 2020 |
| Simplifying TugGraph using zipping algorithms S Golodetz, A Arnab, ID Voiculescu, SA Cameron Pattern Recognition 103, 107257, 2020 | | 2020 |
