• More information about our seminar in SS'20 can be found here

• 3D reconstruction and analysis of rigid and non-rigid scenes and objects
• point set registration and transformation estimation
• new sensors and hardware for computer graphics and vision
• physics-based methods

2020

A Quantum Computational Approach to Correspondence Problems on Point Sets. V. Golyanik and C. Theobalt. In Computer Vision and Pattern Recognition (CVPR), 2020. [paper] [slides] [poster] [bibtex] [arXiv] [project page]

EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera. L. Xu, W. Xu, V. Golyanik, M. Habermann, L. Fang and C. Theobalt. In Computer Vision and Pattern Recognition (CVPR), 2020; Oral [paper] [supplement] [bibtex] [arXiv] [project page]

HandVoxNet: Deep Voxel-Based Network for 3D Hand Shape and Pose Estimation from a Single Depth Map. J. Malik, I. Abdelaziz, A. Elhayek, S. Shimada, S. A. Ali, V. Golyanik, C. Theobalt and D. Stricker. In Computer Vision and Pattern Recognition (CVPR), 2020. [paper] [supplement] [bibtex] [arXiv] [project page]

Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds. V. Golyanik. Springer Vieweg Verlag. 2020. [Springer] [Springer Link] [Book Flyer]

2019

Intrinsic Dynamic Shape Prior for Fast, Sequential and Dense Non-Rigid Structure from Motion with Detection of Temporally-Disjoint Rigidity. V. Golyanik, A. Jonas, D. Stricker and C. Theobalt. arXiv.org, 2019. [bibtex] [arXiv] [project page]

Structure from Articulated Motion: Accurate and Stable Monocular 3D Reconstruction without Training Data. O. Kovalenko, V. Golyanik, J. Malik, A. Elhayek and D. Stricker. Sensors (Volume 19, Issue 20), 2019. [paper] [link (open access)] [video] [bibtex] [arXiv]

Accelerated Gravitational Point Set Alignment with Altered Physical Laws. V. Golyanik, C. Theobalt and D. Stricker. International Conference on Computer Vision (ICCV), 2019; [paper] [supplementary material] [poster] [bibtex] [project page]

A Shape Completion Component for Monocular Non-Rigid SLAM. Y. Su, V. Golyanik, N. Minaskan, S. A. Ali and D. Stricker. International Symposium on Mixed and Augmented Reality (ISMAR), 2019. [paper] [supplement (video, 15 MB)] [MSCC Dataset] [bibtex]

DispVoxNets: Non-Rigid Point Set Alignment with Supervised Learning Proxies. S. Shimada, V. Golyanik, E. Tretschk, D. Stricker and C. Theobalt. In International Conference on 3D Vision (3DV), 2019; Oral [paper] [poster] [presentation] [project page] [arXiv] [bibtex]

Optimising for Scale in Globally Multiply-Linked Gravitational Point Set Registration Leads to Singularities. V. Golyanik and C. Theobalt. In International Conference on 3D Vision (3DV), 2019; Spotlight [paper] [supplement (pdf)] [poster] [video] [bibtex]

DEMEA: Deep Mesh Autoencoders for Non-Rigidly Deforming Objects. E. Tretschk, A. Tewari, M. Zollhöfer, V. Golyanik and C. Theobalt. arXiv.org, 2019. [bibtex] [arXiv] [project page]

FACE IT!: A Pipeline For Real-Time Performance-Driven Facial Animation. J. M. Dı́az Barros, V. Golyanik, K. Varanasi and D. Stricker. International Conference on Image Processing ICIP, 2019; Oral (Lecture) [paper] [bibtex]

IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction. S. Shimada, V. Golyanik, C. Theobalt and D. Stricker. Computer Vision and Pattern Recognition Workshops (Photogrammetric Computer Vision Workshop), 2019; Oral [paper] [bibtex] [arXiv] [project page]

Consolidating Segmentwise Non-Rigid Structure from Motion. V. Golyanik, A. Jonas and D. Stricker. Machine Vision Applications (MVA), 2019; Oral [paper] [bibtex] [poster] [conference talk (11.5 minutes, 130 MB)]

2018

NRGA: Gravitational Approach for Non-Rigid Point Set Registration. S. A. Ali. V. Golyanik and D. Stricker. International Conference on 3D Vision (3DV), 2018; Oral [paper] [supplementary video] [poster] [bibtex]

HDM-Net: Monocular Non-Rigid 3D Reconstruction with Learned Deformation Model. V. Golyanik, S. Shimada, K. Varanasi and D. Stricker. EuroVR, 2018; Oral (Long Paper) [paper] [HDM-Net data set] [bibtex]

Improving Time-Of-Flight Sensor for Specular Surfaces With Shape from Polarozation. T. Yoshida, V. Golyanik, O. Wasenmüller and D. Stricker. International Conference on Image Processing (ICIP), 2018. [paper] [bibtex]

Classification of LIDAR Sensor Contaminations with Deep Neural Networks. J. K. James, G. Puhlfürst, V. Golyanik and D. Stricker. ACM Chapters Computer Science in Cars Symposium (CSCS), 2018; Oral [paper] [bibtex]

2017

Multiframe Scene Flow with Piecewise Rigid Motion. V. Golyanik, K. Kim, R. Maier, M. Nießner, D. Stricker and J. Kautz. International Conference on 3D Vision (3DV), 2017; Spotlight Oral [paper] [arXiv] [supplementary material] [poster] [bibtex]

Scalable Dense Monocular Surface Reconstruction. M.D.Ansari, V. Golyanik and D. Stricker. International Conference on 3D Vision (3DV), 2017. [paper] [arXiv] [bibtex]

High-Dimensional Model for Dense Monocular Surface Recovery. V. Golyanik and D. Stricker. International Conference on 3D Vision (3DV), 2017. [paper] [bibtex]

Introduction to Coherent Depth Fields for Dense Monocular Surface Recovery. V. Golyanik, T. Fetzer and D. Stricker. British Machine Vision Conference (BMVC), 2017. [paper] [supplementary video] [bibtex]

Towards Scheduling Hard Real-Time Image Processing Tasks on a Single GPU. V. Golyanik, M. Nasri and D. Stricker. International Conference on Image Processing (ICIP), 2017. [paper] [bibtex]

A Framework for an Accurate Point Cloud Based Registration of Full 3D Human Body Scans. V. Golyanik, G. Reis, B. Taetz and D. Stricker. Machine Vision Applications (MVA), 2017. [paper] [bibtex]

Dense Batch Non-Rigid Structure from Motion in a Second. V. Golyanik and D. Stricker. Winter Conference on Applications of Computer Vision (WACV), 2017. [paper] [supplementary video] [poster] [bibtex]

Accurate 3D Reconstruction of Dynamic Scenes from Monocular Image Sequences with Severe Occlusions. V. Golyanik, T. Fetzer and D. Stricker. Winter Conference on Applications of Computer Vision (WACV), 2017. [paper] [supplementary material] [poster] [arXiv] [bibtex]

2016

NRSfM-Flow: Recovering Non-Rigid Scene Flow from Monocular Image Sequences. V. Golyanik, A. S. Mathur and D. Stricker. British Machine Vision Conference (BMVC), 2016. [paper] [extended abstract] [poster] [supplementary video] [bibtex]

Joint Pre-Alignment and Robust Rigid Point Set Registration. V. Golyanik, B. Taetz and D. Stricker. International Conference on Image Processing (ICIP), 2016. [paper] [bibtex]

Gravitational Approach for Point Set Registration. V. Golyanik, S. A. Ali and D. Stricker. Computer Vision and Pattern Recognition (CVPR), 2016. [paper] [supplementary material] [bibtex]

Extended Coherent Point Drift Algorithm with Correspondence Priors and Optimal Subsampling. V. Golyanik, B. Taetz, G. Reis and D. Stricker. Winter Conference on Applications of Computer Vision (WACV), 2016. [paper] [poster] [bibtex]

Occlusion-Aware Video Registration for Highly Non-Rigid Objects. B. Taetz, G. Bleser, V. Golyanik and D. Stricker. Winter Conference on Applications of Computer Vision (WACV), 2016. Best Paper Award. [paper] [supplementary material] [bibtex]

2015

Precise and Automatic Anthropometric Measurement Extraction using Template Registration. O. Wasenmüller, J. C. Peters, V. Golyanik and D. Stricker. International Conference on 3D Body Scanning Technologies (3DBST), 2015. [paper] [bibtex]

• since Sept.2018:
  Researcher at Max Planck Institute (MPI) for Informatics
• Jan.2016 - Sept.2018:
  Researcher at German Center for Artificial Intelligence (DFKI),
  Augmented Vision Department, Kaiserslautern, Germany
• Oct.2016 - April.2017:
  Visiting Research Intern at NVIDIA, Santa Clara, CA, USA
• March.2014 - Dec.2015:
  Researcher at the University of Kaiserslautern, Department of Computer Science,
  Augmented Vision Lab (operated in cooperation with DFKI)