Alexander Kirillov

 

I am 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

 

Publications

game Exploring Randomly Wired Neural Networks for Image Recognition
Saining Xie, Alexander Kirillov, Ross Girshick, Kaiming He
technical report, 2019
game Panoptic Feature Pyramid Networks
Alexander Kirillov, Ross Girshick, Kaiming He, Piotr Dollàr
CVPR, 2019, Oral
game Panoptic Segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Piotr Dollàr
CVPR, 2019
game 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
game InstanceCut: from Edges to Instances with MultiCut
Alexander Kirillov, Evgeny Levinkov, Bjoern Andres, Bogdan Savchynskyy, Carsten Rother
CVPR, 2017
game Global hypothesis generation for 6D object pose estimation
Frank Michel, Alexander Kirillov, Eric Brachmann, Alexander Krull, Stefan Gumhold, Bogdan Savchynskyy, Carsten Rother
CVPR, 2017
game 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
game 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
game A Comparative Study of Local Search Algorithms for Correlation Clustering
Evgeny Levinkov, Alexander Kirillov, Bjoern Andres
GCPR, 2017
game Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization
Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy
NIPS, 2016
game Deep Part-Based Generative Shape Model with Latent Variables
Alexander Kirillov, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, Dmitry Vetrov
BMVC, 2016
game 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
game M-Best-Diverse Labelings for Submodular Energies and Beyond
Alexander Kirillov, Dmitrij Schlesinger, Dmitry P Vetrov, Carsten Rother, Bogdan Savchynskyy
NIPS, 2015
game Inferring M-Best Diverse Labelings in a Single One
Alexander Kirillov, Bogdan Savchynskyy, Dmitrij Schlesinger, Dmitry P Vetrov, Carsten Rother,
ICCV, 2015

 

Talks

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