Machine Learning

We work on algorithms for finding hidden structure in large data sets, using a combination of probabilistic modeling and deep learning, ranging from social media understanding, text mining, and consumer analytics to visual computing and content generation.

Latest Publications

Factorized Motion Diffusion for Precise and Character-Agnostic Motion Inbetweening

November 21, 2024
Motion, Interaction and Games (2024)

Justin Studer (DisneyResearch|Studios/ETH Zurich)
Dhruv Agrawal (DisneyResearch|Studios/ETH Zurich)
Dominik Borer (DisneyResearch|Studios)
Seyedmorteza Sadat (DisneyResearch|Studios/ETH Zurich)
Robert W. Sumner (DisneyResearch|Studios/ETH Zurich)
Martin Guay (DisneyResearch|Studios)
Jakob Buhmann (DisneyResearch|Studios)

Controllable Inversion of Black-Box Face Recognition Models via Diffusion

October 2, 2023, Workshop on Analysis and Modeling of Faces and Gestures 2023

Manuel Kansy (DisneyResearch|Studios/ETH Joint PhD)
Anton Rael  (ETH Zurich)
Graziana Mignone (DisneyResearch|Studios)
Jacek Naruniec (DisneyResearch|Studios)
Christopher Schroers (DisneyResearch|Studios)
Markus Gross (DisneyResearch|Studios /ETH Zurich)
Romann M. Weber (DisneyResearch|Studios)