| Panoptic segmentation A Kirillov, K He, R Girshick, C Rother, P Dollár Proceedings of the IEEE conference on computer vision and pattern …, 2019 | 274 | 2019 |
| Detectron2 Y Wu, A Kirillov, F Massa, WY Lo, R Girshick | 236* | 2019 |
| Panoptic Feature Pyramid Networks A Kirillov, R Girshick, K He, P Dollár arXiv preprint arXiv:1901.02446, 2019 | 200 | 2019 |
| Exploring randomly wired neural networks for image recognition S Xie, A Kirillov, R Girshick, K He Proceedings of the IEEE International Conference on Computer Vision, 1284-1293, 2019 | 162 | 2019 |
| 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 | 145 | 2017 |
| End-to-End Object Detection with Transformers N Carion, F Massa, G Synnaeve, N Usunier, A Kirillov, S Zagoruyko arXiv preprint arXiv:2005.12872, 2020 | 98 | 2020 |
| 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), 2016 | 90 | 2016 |
| 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 | 78 | 2017 |
| 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 | 71 | 2018 |
| 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 | 51 | 2017 |
| 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 | 46 | 2020 |
| Inferring M-Best Diverse Labelings in a Single One A Kirillov, B Savchynskyy, D Schlesinger, D Vetrov, C Rother The IEEE International Conference on Computer Vision (ICCV), 2015 | 42 | 2015 |
| 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 | 41* | 2016 |
| M-Best-Diverse Labelings for Submodular Energies and Beyond A Kirillov, D Shlezinger, DP Vetrov, C Rother, B Savchynskyy Advances in Neural Information Processing Systems (NIPS), 613-621, 2015 | 23 | 2015 |
| A Comparative Study of Local Search Algorithms for Correlation Clustering E Levinkov, A Kirillov, B Andres German Conference on Pattern Recognition (GCPR), 103-114, 2017 | 18 | 2017 |
| Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization A Kirillov, A Shekhovtsov, C Rother, B Savchynskyy Advances in Neural Information Processing Systems (NIPS), 334-342, 2016 | 11 | 2016 |
| A unified architecture for instance and semantic segmentation A Kirillov, K He, R Girshick, P Dollár | 10 | 2017 |
| Linear combination of random forests for the Relevance Prediction Challenge M Figurnov, A Kirillov Proc. of Int. Conf. on Web Service and Data Mining workshop on Web Search …, 2012 | 6 | 2012 |
| Deep Part-Based Generative Shape Model with Latent Variables A Kirillov, M Gavrikov, E Lobacheva, A Osokin, D Vetrov British Machine Vision Conference (BMVC), 2016 | 1 | 2016 |
| TrackFormer: Multi-Object Tracking with Transformers T Meinhardt, A Kirillov, L Leal-Taixe, C Feichtenhofer arXiv preprint arXiv:2101.02702, 2021 | | 2021 |
Carsten RotherProfessor Uni Heidelberg / GermanyVerified email at iwr.uni-heidelberg.de
