A | B | C | D | E | F 
 G | H | I | J | K | L | M 
 N | O | P | Q | R | S | T 
 U | V | W | X | Y | Z 
max planck institut
mpii logo Minerva of the Max Planck Society


Sotnychenko, Oleksandr

Oleksandr Sotnychenko

Max-Planck-Institut für Informatik
Saarland Informatics Campus
Department 6: Visual Computing and Artificial Intelligence Campus E1 4, Room 217
66123 Saarbrücken

Email: Get my email address via email
Phone: +49 681 9325 4017

Research Interests


VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera

D. Mehta S. Sridhar O. Sotnychenko H. Rhodin M. Shafiei H. Seidel W. Xu D. Casas C. Theobalt

Special Interest Group on Computer GRAPHics and Interactive Technique (SIGGRAPH) 2017

We present the first real-time method to capture the full global 3D skeletal pose of a human in a stable, temporally consistent manner using a single RGB camera.

[project page]

Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision

D. Mehta H. Rhodin D. Casas O. Sotnychenko W. Xu C. Theobalt

International Conference on 3D Vision (3DV) 2017

We propose a CNN-based approach for 3D human body pose estimation from single RGB images that addresses the issue of limited generalizability of models trained solely on the starkly limited publicly available 3D pose data.

[project page]

Real-time Hand Tracking under Occlusion from an Egocentric RGB-D Sensor

F. Mueller D. Mehta O. Sotnychenko S. Sridhar D. Casas C. Theobalt

International Conference on Computer Vision (ICCV) 2017

We present a method for real-time hand tracking under occlusion in cluttered egocentric scenes from a single RGB-D camera. To enable training of our machine learning components, we introduce a new large-scale dataset SynthHands which was captured using a mixed reality approach. Furthermore, we propose a real benchmark dataset EgoDexter which provides annotated fingertip positions.

[project page]