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