by Martina Megaro | Jul 3, 2023 | Capture, Machine Learning, VFX
Graph-Based Synthesis for Skin Micro Wrinkles We present a novel graph-based simulation approach for generating micro wrinkle geometry on human skin, which can easily scale up to the micro-meter range and millions of wrinkles. July 3, 2023 Eurographics Symposium on...
by Sarah Frigg | Jan 3, 2023 | Capture, Machine Learning, VFX
Self-Supervised Effective Resolution Estimation with Adversarial Augmentations We demonstrate that our method outperforms state-of-the-art image quality assessment methods in estimating the sharpness of real and generated human faces. January 3, 2023 IEEE Winter...
by Sarah Frigg | Nov 30, 2022 | Capture, Machine Learning, VFX
Production-Ready Face Re-Aging for Visual Effects We demonstrate how the simple U-Net, surprisingly, allows us to advance the state of the art for re-aging real faces on video, with unprecedented temporal stability and preservation of facial identity across variable...
by Sarah Frigg | Oct 5, 2022 | Capture, Machine Learning, VFX
Learning Dynamic 3D Geometry and Texture for Video Face Swapping We approach the problem of face swapping from the perspective of learning simultaneous convolutional facial autoencoders for the source and target identities, using a shared encoder network with...
by Sarah Frigg | Sep 13, 2022 | Capture, Machine Learning, VFX
Facial Animation with Disentangled Identity and Motion using Transformers We propose a 3D+time framework for modeling dynamic sequences of 3D facial shapes, representing realistic non-rigid motion during a performance. September 13, 2022ACM/Eurographics Symposium...
by Sarah Frigg | Jul 25, 2022 | Capture, Machine Learning, VFX
Training a Deep Remastering Model We present a deep learning solution to bring the NTSC version to the new scan quality levels, which would be otherwise impossible with existing tools. July 24, 2022ACM SIGGRAPH 2022 Authors Abdelaziz Djelouah...
