Mark Boss

Mark Boss

Research Scientist

Unity Technologies

Biography

Mark Boss is a researcher at Unity Technologies. Before that, he was a Ph.D. student at the University of Tübingen in the computer graphics group of Prof. Hendrik Lensch. His research interests lie at the intersection of machine learning and computer graphics, with the main focus on inferring physical properties (shape, material, illumination, etc.) from images.

If you are interested in a research collaboration, please drop me a    mail with your CV.

Interests
  • Machine Learning
  • Computer Graphics
  • Inverse Rendering
Education

  • MSc in Computer Science, 2018

    University of Tübingen

  • BSc in Computer Science, 2016

    Osnabrück University of Applied Sciences

News

SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
15 Sep 2022 - Accepted at NeurIPS 2022.
An open-source smartphone app for the quantitative evaluation of thin-layer chromatographic analyses in medicine quality screening
04 Aug 2022 - Scientific Report article and Project page online
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
31 May 2022 - ArXiv submission and Project page online
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
19 Oct 2021 - Accepted at NeurIPS 2021 Poster Presentation, arXiv and Project page online
NeRD: Neural Reflectance Decomposition from Image Collections
18 Aug 2021 - Accepted for a ICCV 2021 Poster Presentation
See all

Recent Posts

NeRF at ECCV 2022
I recently went through the the provisional programm of ECCV 2022. After my last post on “NeRF at NeurIPS” got such great feedback, and I anyway compiled a list of all NeRFy things, I decided to do it all again.
Oct 1, 2022 11 min read NeRF, Literature Review
NeRF at NeurIPS 2022
Inspired by Frank Dellaert and his excellent series on the original NeRF Explosion and the following ICCV/CVPR conference gatherings, I decided to look into creating a NeurIPS 22 rundown myself.
Last updated on Sep 30, 2022 8 min read NeRF, Literature Review

Recent & Upcoming Talks

Neural Reflectance Decomposition
Jul 26, 2022 10:00 AM — 11:00 AM Adobe Research
Slides

Publications

An open-source smartphone app for the quantitative evaluation of thin-layer chromatographic analyses in medicine quality screening
Substandard and falsified medicines present a serious threat to public health. Simple, low-cost screening tools are important in the …
Cite Project PDF Code Website
An open-source smartphone app for the quantitative evaluation of thin-layer chromatographic analyses in medicine quality screening
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Inverse rendering of an object under entirely unknown capture conditions is a fundamental challenge in computer vision and graphics. …
Cite arXiv Video
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
Decomposing a scene into its shape, reflectance and illumination is a fundamental problem in computer vision and graphics. Neural …
Cite arXiv Video Code
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
NeRD: Neural Reflectance Decomposition from Image Collections
Decomposing a scene into its shape, reflectance, and illumination is a challenging but important problem in computer vision and …
Cite arXiv Video Code Dataset
NeRD: Neural Reflectance Decomposition from Image Collections
Two-shot Spatially-varying BRDF and Shape Estimation
Capturing the shape and spatially-varying appearance (SVBRDF) of an object from images is a challenging task that has applications in …
Cite Paper + Supplementary arXiv Video Code Dataset
Two-shot Spatially-varying BRDF and Shape Estimation
Single Image BRDF Parameter Estimation with a Conditional Adversarial Network
Creating plausible surfaces is an essential component in achieving a high degree of realism in rendering. To relieve artists, who …
PDF Cite
Single Image BRDF Parameter Estimation with a Conditional Adversarial Network
Deep Dual Loss BRDF Parameter Estimation
Surface parameter estimation is an essential field in computer games and movies. An exact representation of a real-world surface allows …
PDF Cite DOI
Deep Dual Loss BRDF Parameter Estimation

Projects

TLCyzer
TLCyzer is a free and open source smartphone app for the quantitative evaluation of thin-layer chromatographic analyses in medicine quality screening, described and validated in a scientific study.
TLCyzer
farrow-and-ball
A set of British paint manufacturer Farrow & Ball inspired color maps for matplotlib. The maps are sorted in categories for different plotting needs (Divergent, Spectral, Base Colors, Misc).
farrow-and-ball
Online BRDF Visualization
The bidirectional reflectance distribution function (BRDF) is a function that defines how incoming light is reflected outward. This web-based visualizer uses the Cook-Torrance model and shows how the material looks on a sphere, and simultaneously displays its evaluated BRDF. Especially the different reflective behavior of specular and diffuse materials are easily visible.
Online BRDF Visualization
Infomark
A free, scalable, modern and open source solution for programming lectures supporting auto-testing/grading of programming assignments scaling to thousands of students and several courses.
Infomark

Experience

 
 
 
 
 
Unity Technologies
Senior Research Scientist
Unity Technologies
Sep 2022 – Present Germany
Research on object acquisition.
 
 
 
 
 
University of Tübingen
Ph.D. Student
University of Tübingen
Jun 2018 – Jun 2022 Tübingen, Germany
Research on deep learning based material acquisition.
 
 
 
 
 
Google
Student Researcher
Google
Jun 2021 – Apr 2022 Germany (Remote)
Research on novel techniques for material, geometry and illumination disentanglement.
 
 
 
 
 
NVIDIA
Research Intern
NVIDIA
Apr 2019 – Jul 2019 Westford, MA
Research on casual shape and material acquisition, which resulted in the publication: “Two-shot Spatially-varying BRDF and Shape Estimation”
 
 
 
 
 
zahlz
Android Developer
zahlz
Jul 2015 – Jun 2017 Osnabrück
Development of an Android Application for a mobile payment system.