activity
20202022
most citedA high fidelity synthetic face framework for computer vision

4 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Mesh-Tension Driven Expression-Based Wrinkles for Synthetic Faces

Chirag Raman, Charlie Hewitt, Erroll Wood +1

Recent advances in synthesizing realistic faces have shown that synthetic training data can replace real data for various face-related computer vision tasks. A question arises: how…

cs.CV2021

Synthetic Data for Multi-Parameter Camera-Based Physiological Sensing

Daniel McDuff, Xin Liu, Javier Hernandez +2

Synthetic data is a powerful tool in training data hungry deep learning algorithms. However, to date, camera-based physiological sensing has not taken full advantage of these techn…

cs.CV20211 cited

Fake It Till You Make It: Face analysis in the wild using synthetic data alone

Erroll Wood, Tadas Baltrušaitis, Charlie Hewitt +5

We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone. The community has long enjoyed the benefits of synthesizing train…

cs.CV2020

Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars

Daniel McDuff, Javier Hernandez, Erroll Wood +2

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring. However, machine vision approaches are often limited by the availabilit…

cs.CV20204 cited

A high fidelity synthetic face framework for computer vision

Tadas Baltrusaitis, Erroll Wood, Virginia Estellers +6

Analysis of faces is one of the core applications of computer vision, with tasks ranging from landmark alignment, head pose estimation, expression recognition, and face recognition…