Egor Burkov

Graduated from: Skoltech

Research interests: deep learning, computer vision, telepresence, pose estimation, high-performance computing

Thesis title: Novel Human Pose Estimation Algorithms for Telepresence

Publications:

E. Burkov and V. Lempitsky. Deep Neural Networks with Box Convolutions. Advances in Neural Information Processing Systems (NIPS), Montreal, 2018.

A. Shysheya, E. Zakharov, K.-A. Aliev, R. Bashirov, A. Ivakhnenko, E. Burkov, D. Ulyanov, Yu. Malkov, K. Iskakov, I. Pasechnik, A. Vakhitov, V. Lempitsky. Textured Neural Avatars. CVF/IEEE Computer Vision and Pattern Recognition (CVPR) oral, Long Beach, CA, 2019.

K. Iskakov, E. Burkov, V. Lempitsky, Y. Malkov. Learnable Triangulation of Human Pose. CVF/IEEE International Conference on Computer Vision (ICCV) oral, Seoul, 2019.

E. Zakharov, A. Shysheya, E. Burkov, V. Lempitsky. Few-Shot Adversarial Learning of Realistic Neural Talking Head Models. CVF/IEEE International Conference on Computer Vision (ICCV) oral, Seoul, 2019.

Conferences:

“Deep Neural Networks with Box Convolutions” poster presentation, NIPS 2018, Montreal.