Follow
Sergey Prokudin
Sergey Prokudin
Verified email at inf.ethz.ch - Homepage
Title
Cited by
Cited by
Year
Deep directional statistics: Pose estimation with uncertainty quantification
S Prokudin, P Gehler, S Nowozin
Proceedings of the European conference on computer vision (ECCV), 534-551, 2018
982018
Efficient learning on point clouds with basis point sets
S Prokudin, C Lassner, J Romero
The IEEE International Conference on Computer Vision (ICCV), 4332--4341, 2019
852019
SMPLpix: Neural Avatars from 3D Human Models
S Prokudin, MJ Black, J Romero
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
752020
DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks—application to CEST imaging of the human brain at 3T
F Glang, A Deshmane, S Prokudin, F Martin, K Herz, T Lindig, B Bender, ...
Magnetic resonance in medicine 84 (1), 450-466, 2020
642020
Real time trajectory prediction using deep conditional generative models
S Gomez-Gonzalez, S Prokudin, B Schölkopf, J Peters
IEEE Robotics and Automation Letters 5 (2), 970-976, 2020
352020
System and method for generating sets of antivirus records for detection of malware on user devices
SV Prokudin
US Patent 9,654,486, 2017
16*2017
System and method for evaluating malware detection rules
AM Romanenko, IO Tolstikhin, SV Prokudin
US Patent 9,171,155, 2015
92015
Dynamic Point Fields
S Prokudin, Q Ma, M Raafat, J Valentin, S Tang
arXiv preprint arXiv:2304.02626, 2023
82023
HARP: Personalized Hand Reconstruction from a Monocular RGB Video
K Karunratanakul, S Prokudin, O Hilliges, S Tang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
82023
Learning to filter object detections
S Prokudin, D Kappler, S Nowozin, P Gehler
Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017
62017
ResFields: Residual neural fields for spatiotemporal signals
M Mihajlovic, S Prokudin, M Pollefeys, S Tang
arXiv preprint arXiv:2309.03160, 2023
32023
Image generation from 3D model using neural network
S Prokudin, JR Gonzalez-Nicolas, MJ Black
US Patent 11,403,800, 2022
32022
Rapid point cloud alignment and classification with basis set learning
JR Gonzalez-Nicolas, S Prokudin, C Lassner
US Patent 11,176,693, 2021
32021
Machine learning based processing of magnetic resonance data, including an uncertainty quantification
M Zaiss, F Glang, S Prokudin, K Scheffler
US Patent App. 17/111,545, 2022
12022
Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation
X Chen, M Mihajlovic, S Wang, S Prokudin, S Tang
arXiv preprint arXiv:2401.04728, 2024
2024
Robust and efficient deep visual learning
S Prokudin
Universität Tübingen, 2020
2020
DeepCEST 3T: Robust neural network prediction of 3T CEST MRI parameters including uncertainty quantification
F Glang, A Deshmane, S Prokudin, F Martin, K Herz, T Lindig, B Bender, ...
2020 ISMRM & SMRT Virtual Conference & Exhibition, 216, 2020
2020
Dynamic Point Fields Supplementary Material
S Prokudin, Q Ma, M Raafat, J Valentin, S Tang
The system can't perform the operation now. Try again later.
Articles 1–18