17 citations · 25 across the 5 of their papers we have counts for
4 papers · 1 filter
DAViD: Data-efficient and Accurate Vision Models from Synthetic Data
Fatemeh Saleh, Sadegh Aliakbarian, Charlie Hewitt +5
The state of the art in human-centric computer vision achieves high accuracy and robustness across a diverse range of tasks. The most effective models in this domain have billions…
Look Ma, no markers: holistic performance capture without the hassle
Charlie Hewitt, Fatemeh Saleh, Sadegh Aliakbarian +8
We tackle the problem of highly-accurate, holistic performance capture for the face, body and hands simultaneously. Motion-capture technologies used in film and game production typ…
GeoGen: Geometry-Aware Generative Modeling via Signed Distance Functions
Salvatore Esposito, Qingshan Xu, Kacper Kania +6
We introduce a new generative approach for synthesizing 3D geometry and images from single-view collections. Most existing approaches predict volumetric density to render multi-vie…
Procedural Humans for Computer Vision
Charlie Hewitt, Tadas Baltrušaitis, Erroll Wood +3
Recent work has shown the benefits of synthetic data for use in computer vision, with applications ranging from autonomous driving to face landmark detection and reconstruction. Th…