Michael Niemeyer
Michael Niemeyer
Max Planck Institute for Intelligent Systems and University of Tübingen
Verified email at tue.mpg.de - Homepage
Title
Cited by
Cited by
Year
Occupancy networks: Learning 3d reconstruction in function space
L Mescheder, M Oechsle, M Niemeyer, S Nowozin, A Geiger
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
2532019
Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
M Niemeyer, L Mescheder, M Oechsle, A Geiger
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
312020
Texture fields: Learning texture representations in function space
M Oechsle, L Mescheder, M Niemeyer, T Strauss, A Geiger
Proceedings of the IEEE International Conference on Computer Vision, 4531-4540, 2019
292019
Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics
M Niemeyer, L Mescheder, M Oechsle, A Geiger
Proceedings of the IEEE International Conference on Computer Vision, 5379-5389, 2019
162019
Convolutional Occupancy Networks
S Peng, M Niemeyer, L Mescheder, M Pollefeys, A Geiger
arXiv preprint arXiv:2003.04618, 2020
102020
Automatic Semantic Labelling of Images by Their Content Using Non-Parametric Bayesian Machine Learning and Image Search Using Synthetically Generated Image Collages
M Niemeyer, O Arandjelović
2018 IEEE 5th International Conference on Data Science and Advanced …, 2018
62018
Learning Implicit Surface Light Fields
M Oechsle, M Niemeyer, L Mescheder, T Strauss, A Geiger
arXiv preprint arXiv:2003.12406, 2020
32020
GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
K Schwarz, Y Liao, M Niemeyer, A Geiger
Advances in Neural Information Processing Systems 33, 2020
22020
Supplementary Material for Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics
M Niemeyer, L Mescheder, M Oechsle, A Geiger
Supplementary Material for Occupancy Networks: Learning 3D Reconstruction in Function Space
L Mescheder, M Oechsle, M Niemeyer, S Nowozin, A Geiger
Supplementary Material for Texture Fields: Learning Texture Representations in Function Space
M Oechsle, L Mescheder, M Niemeyer, T Strauss, A Geiger
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Articles 1–11