Alexander Kirillov

I am leading multimodal research group in OpenAI Previously, a research scientist at Facebook AI Research (FAIR) working on computer vision. I received my PhD from Heidelberg University, Germany, under the supervision of Carsten Rother. I did my diploma at Lomonosov Moscow State University, Russia, where I worked with Dmitry Vetrov and Alexander Dyakonov.

Email / Biography / Google Scholar

News

I have joined OpenAI to lead multimodal research group..
We released the segment anything project. Check out our interactive demo, the new dataset with 1.1B masks, and the code.
I will be serving as an area chair for CVPR 2023 and ICCV 2023
We received the PAMI Mark Everingham award for Detectron2
We released the code for DETR

Publications

	Segment Anything Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alex C. Berg, Wan-Yen Lo, Piotr Dollàr, Ross Girshick ICCV, 2023, Oral paper / project / code / dataset
	SLIP: Self-supervision meets Language-Image Pre-training Norman Mu, Alexander Kirillov, David Wagner, Saining Xie ECCV, 2022 arxiv / code
	Masked-attention Mask Transformer for Universal Image Segmentation Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar CVPR, 2022 arxiv / code / project
	Pointly-Supervised Instance Segmentation Bowen Cheng, Omkar Parkhi, Alexander Kirillov CVPR, 2022, Oral arxiv / code / project
	TrackFormer: Multi-Object Tracking with Transformers Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph Feichtenhofer CVPR, 2022 arxiv / code
	Point-Level Region Contrast for Object Detection Pre-Training Yutong Bai, Xinlei Chen, Alexander Kirillov, Alan Yuille, Alexander C Berg CVPR, 2022, Oral arxiv
	Per-Pixel Classification is Not All You Need for Semantic Segmentation Bowen Cheng, Alexander G. Schwing, Alexander Kirillov NeurIPS, 2021, Spotlight arxiv / code / project
	On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness Eric Mintun, Alexander Kirillov, Saining Xie NeurIPS, 2021 arxiv / code
	Boundary IoU: Improving Object-Centric Image Segmentation Evaluation Bowen Cheng, Ross Girshick, Piotr Dollar, Alexander C. Berg, Alexander Kirillov, CVPR, 2021 arxiv / code / project
	DETR: End-to-End Object Detection with Transformers Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko ECCV, 2020, Oral arxiv / code
	PointRend: Image Segmentation as Rendering Alexander Kirillov, Yuxin Wu, Kaiming He, Ross Girshick CVPR, 2020, Oral arxiv / code
	Exploring Randomly Wired Neural Networks for Image Recognition Saining Xie, Alexander Kirillov, Ross Girshick, Kaiming He ICCV, 2019, Oral arxiv
	Panoptic Feature Pyramid Networks Alexander Kirillov, Ross Girshick, Kaiming He, Piotr Dollàr CVPR, 2019, Oral arxiv / code
	Panoptic Segmentation Alexander Kirillov, Kaiming He, Ross Girshick, Piotr Dollàr CVPR, 2019 arxiv / evaluation code
	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 Torr IEEE Signal Processing Magazine, 2018
	InstanceCut: from Edges to Instances with MultiCut Alexander Kirillov, Evgeny Levinkov, Bjoern Andres, Bogdan Savchynskyy, Carsten Rother CVPR, 2017 arxiv
	Global hypothesis generation for 6D object pose estimation Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother CVPR, 2017 arxiv
	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 CVPR, 2017 arxiv
	Analyzing Modular CNN Architectures for Joint Depth Prediction and Semantic Segmentation Omid Hosseini Jafari, Oliver Groth, Alexander Kirillov, Michael Ying Yang, Carsten Rother ICRA, 2017 arxiv
	A Comparative Study of Local Search Algorithms for Correlation Clustering Evgeny Levinkov, Alexander Kirillov, Bjoern Andres GCPR, 2017
	Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy NIPS, 2016 arxiv
	Deep Part-Based Generative Shape Model with Latent Variables Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry Vetrov BMVC, 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 ACCV, 2016 arxiv
	M-Best-Diverse Labelings for Submodular Energies and Beyond Alexander Kirillov, Dmitrij Schlesinger, Dmitry P Vetrov, Carsten Rother, Bogdan Savchynskyy NIPS, 2015
	Inferring M-Best Diverse Labelings in a Single One Alexander Kirillov, Bogdan Savchynskyy, Dmitrij Schlesinger, Dmitry P Vetrov, Carsten Rother, ICCV, 2015

Talks

Unification of Image-level Segmentation Tasks
6th Workshop on Benchmarking Multi-Target Tracking at ICCV 2021

Pixel-level Recogition
Tutorial on Visual Recognition and Beyond at CVPR 2020

Panoptic Segmentation: Task and Approaches
Tutorial on Visual Recognition and Beyond at CVPR 2019

Panoptic Segmentation: Unifying Semantic and Instance Segmentations
Tutorial on Visual Recognition and Beyond at ECCV 2018

COCO-stuff Challenge Winner Talk
Joint Workshop of the COCO and Places Challenges at ICCV 2017

Generating Diverse Solutions from a Single Model
Tutorial on Diversity meets Deep Networks - Inference, Ensemble Learning, and Applications at CVPR 2016

Thanks for the template