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

Improved Lighting Models for Facial Appearance Capture

April 25, 2022
Eurographics 2022

Yingyan Xu (DRZ/ETH Joint M.Sc.) Jérémy Riviere (DisneyResearch|Studios) Gaspard Zoss (DisneyResearch|Studios/ETH Joint PhD) Prashanth Chandran (DisneyResearch|Studios/ETH Joint PhD) Derek Bradley (DisneyResearch|Studios) Paulo Gotardo (DisneyResearch|Studios)

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)