| Normalized cut loss for weakly-supervised CNN segmentation M Tang, A Djelouah, F Perazzi, Y Boykov, C Schroers Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 391 | 2018 |
| On regularized losses for weakly-supervised cnn segmentation M Tang, F Perazzi, A Djelouah, I Ben Ayed, C Schroers, Y Boykov Proceedings of the European Conference on Computer Vision (ECCV), 507-522, 2018 | 374 | 2018 |
| Grabcut in one cut M Tang, L Gorelick, O Veksler, Y Boykov Proceedings of the IEEE International Conference on Computer Vision, 1769-1776, 2013 | 312 | 2013 |
| Constrained-CNN losses for weakly supervised segmentation H Kervadec, J Dolz, M Tang, E Granger, Y Boykov, IB Ayed Medical image analysis 54, 88-99, 2019 | 307 | 2019 |
| FroDO: From Detections to 3D Objects M Runz, K Li, M Tang, L Ma, C Kong, T Schmidt, I Reid, L Agapito, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 72 | 2020 |
| Kernel Cuts: Kernel and Spectral Clustering Meet Regularization M Tang, D Marin, I Ben Ayed, Y Boykov International Journal of Computer Vision 127, 477-511, 2019 | 53* | 2019 |
| Kernel clustering: density biases and solutions D Marin, M Tang, IB Ayed, Y Boykov IEEE transactions on pattern analysis and machine intelligence 41 (1), 136-147, 2017 | 53 | 2017 |
| Pseudo-bound optimization for binary energies M Tang, I Ben Ayed, Y Boykov Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 52 | 2014 |
| Improved delay-range-dependent stability criteria for linear systems with interval time-varying delays M Tang, YW Wang, C Wen IET Control Theory & Applications 6 (6), 868-873, 2012 | 51 | 2012 |
| Secrets of GrabCut and Kernel K-means M Tang, I Ben Ayed, D Marin, Y Boykov Proceedings of the IEEE International Conference on Computer Vision, 1555-1563, 2015 | 46 | 2015 |
| Beyond gradient descent for regularized segmentation losses D Marin, M Tang, IB Ayed, Y Boykov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 39 | 2019 |
| Normalized cut meets MRF M Tang, D Marin, IB Ayed, Y Boykov Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 34 | 2016 |
| Latent space editing in transformer-based flow matching VT Hu, W Zhang, M Tang, P Mettes, D Zhao, C Snoek Proceedings of the AAAI Conference on Artificial Intelligence 38 (3), 2247-2255, 2024 | 26 | 2024 |
| Scribblegen: generative data augmentation improves scribble-supervised semantic segmentation J Schnell, J Wang, L Qi, VT Hu, M Tang arXiv preprint arXiv:2311.17121, 2023 | 4 | 2023 |
| Generative data augmentation improves scribble-supervised semantic segmentation J Schnell, J Wang, L Qi, VT Hu, M Tang CoRR, 2023 | 4 | 2023 |
| Training Class-Imbalanced Diffusion Model Via Overlap Optimization D Yan, L Qi, VT Hu, MH Yang, M Tang arXiv preprint arXiv:2402.10821, 2024 | 3 | 2024 |
| Decepticon: Attacking Secrets of Transformers M Al Rafi, Y Feng, F Yao, M Tang, H Jeon 2023 IEEE International Symposium on Workload Characterization (IISWC), 128-139, 2023 | 2 | 2023 |
| Self-Cross Diffusion Guidance for Text-to-Image Synthesis of Similar Subjects W Qiu, J Wang, M Tang arXiv preprint arXiv:2411.18936, 2024 | | 2024 |
| ReDistill: Residual Encoded Distillation for Peak Memory Reduction F Chen, G Datta, MA Rafi, H Jeon, M Tang arXiv preprint arXiv:2406.03744, 2024 | | 2024 |
| Optimization for Image Segmentation M Tang University of Waterloo, 2019 | | 2019 |
Yuri BoykovProfessor, Computer Science, University of WaterlooVerified email at uwaterloo.ca
