| End-to-end object detection with transformers N Carion, F Massa, G Synnaeve, N Usunier, A Kirillov, S Zagoruyko Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 6287 | 2020 |
| Detectron2 Y Wu, A Kirillov, F Massa, WY Lo, R Girshick | 1974* | 2019 |
| Panoptic segmentation A Kirillov, K He, R Girshick, C Rother, P Dollár Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 1084 | 2019 |
| Panoptic Feature Pyramid Networks A Kirillov, R Girshick, K He, P Dollár Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 926 | 2019 |
| Pointrend: Image segmentation as rendering A Kirillov, Y Wu, K He, R Girshick Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 601 | 2020 |
| Per-pixel classification is not all you need for semantic segmentation B Cheng, A Schwing, A Kirillov Advances in Neural Information Processing Systems 34, 17864-17875, 2021 | 450 | 2021 |
| Masked-attention mask transformer for universal image segmentation B Cheng, I Misra, AG Schwing, A Kirillov, R Girdhar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 360 | 2022 |
| Exploring randomly wired neural networks for image recognition S Xie, A Kirillov, R Girshick, K He Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 354 | 2019 |
| Trackformer: Multi-object tracking with transformers T Meinhardt, A Kirillov, L Leal-Taixe, C Feichtenhofer Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 350 | 2022 |
| InstanceCut: from Edges to Instances with MultiCut A Kirillov, E Levinkov, B Andres, B Savchynskyy, C Rother IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 276 | 2017 |
| Slip: Self-supervision meets language-image pre-training N Mu, A Kirillov, D Wagner, S Xie Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 153 | 2022 |
| 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 | 143 | 2018 |
| Segment anything A Kirillov, E Mintun, N Ravi, H Mao, C Rolland, L Gustafson, T Xiao, ... arXiv preprint arXiv:2304.02643, 2023 | 139 | 2023 |
| Global hypothesis generation for 6D object pose estimation F Michel, A Kirillov, E Brachmann, A Krull, S Gumhold, B Savchynskyy, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 137 | 2017 |
| Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications E Levinkov, J Uhrig, S Tang, M Omran, E Insafutdinov, A Kirillov, C Rother, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 127 | 2017 |
| Boundary iou: Improving object-centric image segmentation evaluation B Cheng, R Girshick, P Dollár, AC Berg, A Kirillov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 118 | 2021 |
| Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation OH Jafari, O Groth, A Kirillov, MY Yang, C Rother IEEE International Conference on Robotics and Automation (ICRA), 2017, 2017 | 75 | 2017 |
| Pointly-supervised instance segmentation B Cheng, O Parkhi, A Kirillov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 53 | 2022 |
| End-to-end object detection with transformers. arXiv 2020 N Carion, F Massa, G Synnaeve, N Usunier, A Kirillov, S Zagoruyko arXiv preprint arXiv:2005.12872, 2005 | 51 | 2005 |
| Joint Training of Generic CNN-CRF Models with Stochastic Optimization A Kirillov, D Schlesinger, S Zheng, B Savchynskyy, PHS Torr, C Rother The 13th Asian Conference on Computer Vision (ACCV), 2016 | 47* | 2016 |
Ross GirshickResearch Scientist, Facebook AI Research (FAIR)Verified email at eecs.berkeley.edu
