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Christoph Lassner

Research Scientist

Meta Reality Labs Research

Biography

I am a Machine Learning and Computer Vision researcher making machines understand and generate representations of humans in 2D and 3D. I joined Facebook Reality Labs in March 2019 to make my vision of better and easier interaction between humans and machines become a reality.

Before joining Facebook, I worked at a startup which was acquired by Amazon. I did my PhD at the Bernstein Center for Computational Neuroscience Tübingen and the Max Planck Institute for Intelligent Systems.

Interests

  • Machine Learning
  • 2D and 3D Human Body Modelling
  • Differentiable and Neural Rendering

Featured Publications

Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Christoph Lassner, Christian Theobalt
September 2021

Non-rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene from Monocular Video

We propose a joined training for neural radiance fields and a deformation field which enables us to do 4D reconstruction over time, even using only a single camera.

PDF Code Project Video
Amit Raj, Julian Tanke, James Hays, Minh Vo, Carsten Stoll, Christoph Lassner
June 2021

ANR: Articulated Neural Rendering for Virtual Avatars

We extend deferred neural rendering to articulated settings, specifically humans, and demonstrate fast and high quality rendering performance.

PDF Project
Christoph Lassner, Michael Zollhöfer
June 2021

Pulsar: Efficient Sphere-based Neural Rendering

A very efficient differentiable renderer, tightly integrated with PyTorch and PyTorch3D.

PDF Code

Recent Publications

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Non-rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene from Monocular Video

We propose a joined training for neural radiance fields and a deformation field which enables us to do 4D reconstruction over time, even using only a single camera.
Edgar Tretschk, Ayush Tewari, Vladislav Golyanik, Michael Zollhöfer, Christoph Lassner, Christian Theobalt
PDF Code Project Video

ANR: Articulated Neural Rendering for Virtual Avatars

We extend deferred neural rendering to articulated settings, specifically humans, and demonstrate fast and high quality rendering performance.
Amit Raj, Julian Tanke, James Hays, Minh Vo, Carsten Stoll, Christoph Lassner
PDF Project

Pulsar: Efficient Sphere-based Neural Rendering

A very efficient differentiable renderer, tightly integrated with PyTorch and PyTorch3D.
Christoph Lassner, Michael Zollhöfer
PDF Code

TexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video

We propose a new method to reconstruct a mesh-based avatar from RGB-D video taking albedo and lighting into account.
Tiancheng Zhi, Christoph Lassner, Tony Tung, Carsten Stoll, Srinivasa G. Narasimhan, Minh Vo
PDF Video

ARCH: Animatable Reconstruction of Clothed Humans

We propose a novel, end-to-end pipeline to reconstruct detailed animatable avatars from a single picture.
Zeng Huang, Yuanlu Xu, Christoph Lassner, Hao Li, Tony Tung
PDF
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