Alexander Kirillov
Alexander Kirillov
Research Scientist, Facebook AI Research (FAIR)
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Y Wu, A Kirillov, F Massa, WY Lo, R Girshick
Panoptic segmentation
A Kirillov, K He, R Girshick, C Rother, P Dollár
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
End-to-end object detection with transformers
N Carion, F Massa, G Synnaeve, N Usunier, A Kirillov, S Zagoruyko
European Conference on Computer Vision, 213-229, 2020
Panoptic Feature Pyramid Networks
A Kirillov, R Girshick, K He, P Dollár
arXiv preprint arXiv:1901.02446, 2019
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
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
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
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
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
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
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
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
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
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
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
A unified architecture for instance and semantic segmentation
A Kirillov, K He, R Girshick, P Dollár
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
TrackFormer: Multi-Object Tracking with Transformers
T Meinhardt, A Kirillov, L Leal-Taixe, C Feichtenhofer
arXiv preprint arXiv:2101.02702, 2021
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
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
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