Graduated from: Skoltech
Research interests: deep learning, computer vision, telepresence, pose estimation, high-performance computing
Thesis title: Novel Human Pose Estimation Algorithms for Telepresence
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.
“Deep Neural Networks with Box Convolutions” poster presentation, NIPS 2018, Montreal.