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 / Twitter / Linkedin

Publications

• 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

• NVIDIA GPU Technology Conference (GTC). 3D Deep Learning in Function Space. San Jose, CA, USA. March 2020.