BodyMap: Learning Full-Body Dense Correspondence Map

no code implementations • CVPR 2022 • Anastasia Ianina, Nikolaos Sarafianos, Yuanlu Xu, Ignacio Rocco, Tony Tung

Dense correspondence between humans carries powerful semantic information that can be utilized to solve fundamental problems for full-body understanding such as in-the-wild surface matching, tracking and reconstruction.

Neural Rendering Novel View Synthesis

StylePeople: A Generative Model of Fullbody Human Avatars

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.

Real-time RGBD-based Extended Body Pose Estimation

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.

Pose Estimation

Free-Lunch Saliency via Attention in Atari Agents

1 code implementation • 7 Aug 2019 • Dmitry Nikulin, Anastasia Ianina, Vladimir Aliev, Sergey Nikolenko

We show experimentally that a network with an FLS module exhibits performance similar to the baseline (i. e., it is "free", with no performance cost) and can be used as a drop-in replacement for reinforcement learning agents.

Decision Making reinforcement-learning +1