Christoph Lassner

Research Scientist

Facebook Reality Labs

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
Human Motion Modelling
Differentiable Rendering

Featured Publications

Nadine Rüegg, Christoph Lassner, Michael J. Black, Konrad Schindler

February 2020

Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

Extending cycle consistency models to learn mappings between 2D images and parameterized 3D models.

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Sergey Prokudin, Christoph Lassner, Javier Romero

October 2019

Efficient Learning on Point Clouds With Basis Point Sets

We propose a novel representation, Basis Point Sets (BPS), for point clouds that allows us to perform deep learning tasks naturally and efficiently.

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Recent Publications

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Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

Extending cycle consistency models to learn mappings between 2D images and parameterized 3D models.

Nadine Rüegg, Christoph Lassner, Michael J. Black, Konrad Schindler

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Efficient Learning on Point Clouds With Basis Point Sets

We propose a novel representation, Basis Point Sets (BPS), for point clouds that allows us to perform deep learning tasks naturally and efficiently.

Sergey Prokudin, Christoph Lassner, Javier Romero

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Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation

We propose a novel end-to-end neural network architecture and training scheme to train 3D body pose and shape estimation from 2D images.

Mohamed Omran, Christoph Lassner, Gerard Pons-Moll, Peter V. Gehler, Bernt Schiele

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Combining Data-Driven 2D and 3D Human Appearance Models

Detailed 2D and 3D body estimation of humans has many applications in our everyday life: interaction with machines, virtual try-on of …

Christoph Lassner

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Towards Accurate Marker-less Human Shape and Pose Estimation over Time

Existing markerless motion capture methods often assume known backgrounds, static cameras, and sequence specific motion priors, …

Yinghao Huang, Federica Bogo, Christoph Lassner, Angjoo Kanazawa, Peter V. Gehler, Javier Romero, Ijaz Akhter, Michael J. Black

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