Synthetic Data: Simulation & Visual Effects at Scale
Gil Elbaz speaks with Tadas Baltrusaitis, who recently released the seminal paper DigiFace 1M: 1 Million Digital Face Images for Face Recognition. Tadas is a true believer in synthetic data and shares his deep knowledge of the subject along with insights on the current state of the field and what CV engineers need to know. Join Gil as they discuss morphable models, multimodal learning, domain gaps, edge cases and more.
TOPICS & TIMESTAMPS
2:06 Getting started in computer science
3:40 Inferring mental states from facial expressions
7:16 Challenges of facial expressions
8:40 Open Face
10:46 MATLAB to Python
13:17 Multimodal Machine Learning
15:52 Multimodals and Synthetic Data
16:54 Morphable Models
22:07 Skill Sets for CV Engineers
25:25 What is Synthetic Data?
27:07 GANs and Diffusion Models
31:24 Fake it Til You Make It
35:25 Domain Gaps
36:32 Long Tails (Edge Cases)
39:42 Training vs. Testing
41:53 Future of NeRF and Diffusion Models
48:26 Avatars and VR/AR
50:39 Advice for Next Generation CV Engineers
51:58 Season One Wrap-Up
LINKS & RESOURCES
Tadas Baltrusaitis, Principal Scientist at Microsoft, Mixed Reality and AI lab in Cambridge, UK
A 3D Morphable Eye Region Model for Gaze Estimation
Multimodal Machine Learning: A Survey and Taxonomy
3d face reconstruction with dense landmarks
Tadas Baltrusaitis is a principal scientist working in the Microsoft Mixed Reality and AI lab in Cambridge UK where he leads the human synthetics team. He recently co-authored the groundbreaking paper DigiFace 1M, a data set of 1 million synthetic images for facial recognition. Tadas is also the co-author of Fake It Till You Make It: Face Analysis in the Wild Using Synthetic Data Alone, among other outstanding papers. Tadas has pushed forward the field of simulated synthetic data in a significant way throughout his career. His PhD research focused on automatic facial expression analysis in difficult real world settings and he was a postdoctoral associate at Carnegie Mellon University where his primary research lay in automatic understanding of human behavior, expressions and mental states using computer vision.
ABOUT THE HOST
I’m Gil Elbaz, co-founder and CTO of Datagen. In this podcast, I speak with interesting computer vision thinkers and practitioners. I ask the big questions that touch on the issues and challenges that ML and CV engineers deal with every day. On the way, I hope you uncover a new subject or gain a different perspective, as well as enjoying engaging conversation. It’s about much more than the technical processes – it’s about people, journeys, and ideas. Turn up the volume, insights inside.