1 code implementation • CVPR 2021 • Artur Grigorev, Karim Iskakov, Anastasia Ianina, Renat Bashirov, Ilya Zakharkin, Alexander Vakhitov, Victor Lempitsky
We show that with the help of neural textures, such avatars can successfully model clothing and hair, which usually poses a problem for mesh-based approaches.
1 code implementation • 5 Mar 2021 • Renat Bashirov, Anastasia Ianina, Karim Iskakov, Yevgeniy Kononenko, Valeriya Strizhkova, Victor Lempitsky, Alexander Vakhitov
We use parametric 3D deformable human mesh model (SMPL-X) as a representation and focus on the real-time estimation of parameters for the body pose, hands pose and facial expression from Kinect Azure RGB-D camera.
no code implementations • 27 Jan 2021 • Rasul Karimov, Yury Malkov, Karim Iskakov, Victor Lempitsky
We have tested the memory layer on the classification, image reconstruction and relocalization problems and found that for some of those, the memory layers can provide significant speed/accuracy improvement with the high utilization of the key-value elements, while others require more careful fine-tuning and suffer from dying keys.
no code implementations • CVPR 2019 • Aliaksandra Shysheya, Egor Zakharov, Kara-Ali Aliev, Renat Bashirov, Egor Burkov, Karim Iskakov, Aleksei Ivakhnenko, Yury Malkov, Igor Pasechnik, Dmitry Ulyanov, Alexander Vakhitov, Victor Lempitsky
In particular, our system estimates an explicit two-dimensional texture map of the model surface.
1 code implementation • ICCV 2019 • Karim Iskakov, Egor Burkov, Victor Lempitsky, Yury Malkov
We present two novel solutions for multi-view 3D human pose estimation based on new learnable triangulation methods that combine 3D information from multiple 2D views.
Ranked #3 on 3D Human Pose Estimation on Panoptic (using extra training data)
no code implementations • 8 Jul 2018 • Karim Iskakov
This paper introduces a semi-parametric approach to image inpainting for irregular holes.