Lars M. Mescheder

According to our database, Lars M. Mescheder authored at least 19 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2020

Stabilität und Expressivität von tiefen generativen Modellen.

Lars M. Mescheder

Proceedings of the Ausgezeichnete Informatikdissertationen 2020., 2020

Stability and Expressiveness of Deep Generative Models.

Lars M. Mescheder

PhD thesis, 2020

Learning Neural Light Transport.

Paul Sanzenbacher, Lars M. Mescheder, Andreas Geiger

CoRR, 2020

Learning Implicit Surface Light Fields.

Michael Oechsle, Michael Niemeyer, Lars M. Mescheder, Thilo Strauss, Andreas Geiger

CoRR, 2020

Convolutional Occupancy Networks.

Songyou Peng, Michael Niemeyer, Lars M. Mescheder, Marc Pollefeys, Andreas Geiger

Proceedings of the Computer Vision - ECCV 2020, 2020

Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision.

Michael Niemeyer, Lars M. Mescheder, Michael Oechsle, Andreas Geiger

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis.

Yiyi Liao, Katja Schwarz, Lars M. Mescheder, Andreas Geiger

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning Implicit Surface Light Fields.

Michael Oechsle, Michael Niemeyer, Christian Reiser, Lars M. Mescheder, Thilo Strauss, Andreas Geiger

Proceedings of the 8th International Conference on 3D Vision, 2020

2019

Texture Fields: Learning Texture Representations in Function Space.

Michael Oechsle, Lars M. Mescheder, Michael Niemeyer, Thilo Strauss, Andreas Geiger

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics.

Michael Niemeyer, Lars M. Mescheder, Michael Oechsle, Andreas Geiger

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Occupancy Networks: Learning 3D Reconstruction in Function Space.

Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, Andreas Geiger

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

An Extended Perona-Malik Model Based on Probabilistic Models.

Lars M. Mescheder, Dirk A. Lorenz

J. Math. Imaging Vis., 2018

Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes.

Hassan Abu Alhaija, Siva Karthik Mustikovela, Lars M. Mescheder, Andreas Geiger, Carsten Rother

Int. J. Comput. Vis., 2018

On the convergence properties of GAN training.

Lars M. Mescheder

CoRR, 2018

Which Training Methods for GANs do actually Converge?

Lars M. Mescheder, Andreas Geiger, Sebastian Nowozin

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

The Numerics of GANs.

Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks.

Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger

Proceedings of the 34th International Conference on Machine Learning, 2017

Augmented Reality meets Deep Learning.

Hassan Abu Alhaija, Siva Karthik Mustikovela, Lars M. Mescheder, Andreas Geiger, Carsten Rother

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring.

Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger

CoRR, 2016