Alexander Kirillov

According to our database, Alexander Kirillov authored at least 33 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

R-MAE: Regions Meet Masked Autoencoders.

Duy-Kien Nguyen, Vaibhav Aggarwal, Yanghao Li, Martin R. Oswald, Alexander Kirillov, Cees G. M. Snoek, Xinlei Chen

CoRR, 2023

Segment Anything.

Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloé Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, Ross B. Girshick

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

SLIP: Self-supervision Meets Language-Image Pre-training.

Norman Mu, Alexander Kirillov, David A. Wagner, Saining Xie

Proceedings of the Computer Vision - ECCV 2022, 2022

TrackFormer: Multi-Object Tracking with Transformers.

Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph Feichtenhofer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Pointly-Supervised Instance Segmentation.

Bowen Cheng, Omkar Parkhi, Alexander Kirillov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Masked-attention Mask Transformer for Universal Image Segmentation.

Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Point-Level Region Contrast for Object Detection Pre-Training.

Yutong Bai, Xinlei Chen, Alexander Kirillov, Alan L. Yuille, Alexander C. Berg

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Mask2Former for Video Instance Segmentation.

Bowen Cheng, Anwesa Choudhuri, Ishan Misra, Alexander Kirillov, Rohit Girdhar, Alexander G. Schwing

CoRR, 2021

Recognizing Scenes from Novel Viewpoints.

Shengyi Qian, Alexander Kirillov, Nikhila Ravi, Devendra Singh Chaplot, Justin Johnson, David F. Fouhey, Georgia Gkioxari

CoRR, 2021

Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details.

Achal Dave, Piotr Dollár, Deva Ramanan, Alexander Kirillov, Ross B. Girshick

CoRR, 2021

On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness.

Eric Mintun, Alexander Kirillov, Saining Xie

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Per-Pixel Classification is Not All You Need for Semantic Segmentation.

Bowen Cheng, Alexander G. Schwing, Alexander Kirillov

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Boundary IoU: Improving Object-Centric Image Segmentation Evaluation.

Bowen Cheng, Ross B. Girshick, Piotr Dollár, Alexander C. Berg, Alexander Kirillov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

End-to-End Object Detection with Transformers.

Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko

Proceedings of the Computer Vision - ECCV 2020, 2020

PointRend: Image Segmentation As Rendering.

Alexander Kirillov, Yuxin Wu, Kaiming He, Ross B. Girshick

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Exploring Randomly Wired Neural Networks for Image Recognition.

Saining Xie, Alexander Kirillov, Ross B. Girshick, Kaiming He

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Panoptic Segmentation.

Alexander Kirillov, Kaiming He, Ross B. Girshick, Carsten Rother, Piotr Dollár

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Panoptic Feature Pyramid Networks.

Alexander Kirillov, Ross B. Girshick, Kaiming He, Piotr Dollár

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Exploring aspects of image segmentation: diversity, global reasoning, and panoptic formulation.

Alexander Kirillov

PhD thesis, 2018

Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction.

Anurag Arnab, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H. S. Torr

IEEE Signal Process. Mag., 2018

WSD-algorithm based on new method of vector-word contexts proximity calculation via epsilon-filtration.

Alexander Kirillov, Natalia Krizhanovsky, Andrew Krizhanovsky

CoRR, 2018

Calculated attributes of synonym sets.

Andrew Krizhanovsky, Alexander Kirillov

CoRR, 2018

2017

Analyzing modular CNN architectures for joint depth prediction and semantic segmentation.

Omid Hosseini Jafari, Oliver Groth, Alexander Kirillov, Michael Ying Yang, Carsten Rother

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

A Comparative Study of Local Search Algorithms for Correlation Clustering.

Evgeny Levinkov, Alexander Kirillov, Bjoern Andres

Proceedings of the Pattern Recognition - 39th German Conference, 2017

Global Hypothesis Generation for 6D Object Pose Estimation.

Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications.

Evgeny Levinkov, Jonas Uhrig, Siyu Tang, Mohamed Omran, Eldar Insafutdinov, Alexander Kirillov, Carsten Rother, Thomas Brox, Bernt Schiele, Bjoern Andres

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

InstanceCut: From Edges to Instances with MultiCut.

Alexander Kirillov, Evgeny Levinkov, Bjoern Andres, Bogdan Savchynskyy, Carsten Rother

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization.

Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Part-Based Generative Shape Model with Latent Variables.

Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry P. Vetrov

Proceedings of the British Machine Vision Conference 2016, 2016

Joint Training of Generic CNN-CRF Models with Stochastic Optimization.

Alexander Kirillov, Dmitrij Schlesinger, Shuai Zheng, Bogdan Savchynskyy, Philip H. S. Torr, Carsten Rother

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

Efficient Likelihood Learning of a Generic CNN-CRF Model for Semantic Segmentation.

Alexander Kirillov, Dmitrij Schlesinger, Walter Forkel, Anatoly Zelenin, Shuai Zheng, Philip H. S. Torr, Carsten Rother

CoRR, 2015

M-Best-Diverse Labelings for Submodular Energies and Beyond.

Alexander Kirillov, Dmytro Shlezinger, Dmitry P. Vetrov, Carsten Rother, Bogdan Savchynskyy

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Inferring M-Best Diverse Labelings in a Single One.

Alexander Kirillov, Bogdan Savchynskyy, Dmitrij Schlesinger, Dmitry P. Vetrov, Carsten Rother

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015