I am Michael Niemeyer, a computer vision PhD student in the Autonomous Vision Group (AVG) @ Max Planck Institute for Intelligent Systems in Tübingen, Germany.
Currently, I am especially interested in continuous 3D representations and generative models.
Scholar / Github / LinkedIn / Twitter
News
- We released a new preprint CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields
- Our GIRAFFE paper got accepted to CVPR 2021
- I was invited to give a talk at the MIT’s seminar on 3D representations
- We released a new pre-print GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
- Our Implicit Surface Light Fields Paper got accepted at 3DV 2020
- Our GRAF Paper got accepted at NeurIPS 2020
- Our Convolutional Occupancy Networks Paper got accepted at ECCV 2020
- I was invited to a give a talk at the Frauenhofer IAO event “100 KI talents”
Publications
- Niemeyer, M., and Geiger, A.. CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields. Arxiv.org. 2021.
- Niemeyer, M., and Geiger, A.. GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.
- Schwarz, K., and Liao, Y., and Niemeyer, M., and Geiger, A.. GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis. Advances in Neural Information Processing Systems (NeurIPS). 2020.
- Peng, S., and Niemeyer, M., and Mescheder, L., and Pollefeys, M., and Geiger, A.. Convolutional Occupancy Networks. Proceedings of the IEEE European Conference on Computer Vision (ECCV). 2020.
- Oechsle, M., and Niemeyer, M., and Mescheder, L., and Strauss, T., and Geiger, A.. Learning Implicit Surface Light Fields. Proceedings of the International Conf. on 3D Vision (3DV). 2020.
- Niemeyer, M., and Mescheder, L., and Oechsle, M., and Geiger, A.. Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.
- Niemeyer, M., and Mescheder, L., and Oechsle, M., and Geiger, A.. Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics. Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2019.
- Oechsle, M., and Mescheder, L., and Niemeyer, M., and Strauss, T., and Geiger, A.. Texture Fields: Learning Texture Representations in Function Space. Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2019.
- Mescheder, L., and Oechsle, M., and Niemeyer, M., and Novozin, S., and Geiger, A. Occupancy networks: Learning 3d reconstruction in function space. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.
- Niemeyer, M., and Arandjelović, O.. Automatic Semantic Labelling of Images by Their Content Using Non-Parametric Bayesian Machine Learning and Image Search Using Synthetically Generated Image Collages. 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). 2018.
Invited Talks
- Massachusetts Institute of Technology. Seminar on 3D Representations. Generative Neural Scene Representations for 3D-Aware Image Synthesis. Cambridge, Massachusetts, USA. January 2021.
- Fraunhofer IAO. 100 KI Talente. KI Forschung und 3D Deep Learning. Stuttgart, BW, Germany. June 2020. Interactive Slides.
- NVIDIA. NVIDIA GPU Technology Conference (GTC). 3D Deep Learning in Function Space. San Jose, CA, USA. March 2020. Interactive Slides.
Education
Oct 2018 | PhD in Computer Vision / Machine Learning International Max Planck Research School for Intelligent Systems |
2016 - 2017 | MSc in Advanced Computer Science University of St Andrews |
2012 - 2015 | BSc in Mathematics University of Cologne |
Awards
Sep 2017 | Dean’s List Award for Academic Excellence University of St Andrews |
Jun 2011 | eFellows.net Scholarship, Admission to German Mathematical Society, Admission to German Physical Society Freiherr-vom-Stein Gymnasium Kleve |