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

Adaptive Convolutions for Structure-Aware Style Transfer

June 19, 2021
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021

Prashanth Chandran (DisneyResearch|Studios/ETH Joint PhD) Gaspard Zoss (DisneyResearch|Studios/ETH Joint PhD) Paulo Gotardo (DisneyResearch|Studios) Markus Gross (DisneyResearch|Studios/ETH Zurich) Derek Bradley (DisneyResearch|Studios)

Semantic Deep Face Models

November 25, 2020
3D International Conference on 3D Vision (3DV) (2020)

Prashanth Chandran (DisneyResearch|Studios/ETH Joint PhD), Derek Bradley (DisneyResearch|Studios), Markus Gross (DisneyResearch|Studios/ETH Zurich), Thabo Beeler (DisneyResearch|Studios)

Interactive Sculpting of Digital Faces Using an Anatomical Modeling Paradigm

July 6, 2020
Eurographics Symposium on Geometry Processing (2020)

Aurel Gruber (DisneyResearch|Studios/ETH Joint M.Sc.) Marco Fratarcangeli (Chalmers University of Technology/DisneyResearch|Studios) Gaspard Zoss (DisneyResearch|Studios/ETH Joint PhD) Roman Cattaneo (DisneyResearch|Studios) Thabo Beeler (DisneyResearch|Studios) Markus Gross (Disney Research/ETH Zurich) Derek Bradley (DisneyResearch|Studios)