ABSTRACT 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 0:00 Introduction 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 19:34 HoloLens 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 LinkedIn Github  Google Scholar Fake it Til You Make It Video  Github Digiface 1M A 3D Morphable Eye Region Model for Gaze Estimation Hololens Multimodal Machine Learning: A Survey and Taxonomy  3d face reconstruction with dense landmarks Open Face Open Face 2.0 Dr. Rana el Kaliouby Dr. Louis-Philippe Morency Peter Robinson Jamie Shotton Errol Wood Affectiva GUEST BIO 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. 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.