by Martina Megaro | Jun 29, 2020 | Capture, Machine Learning
High-Resolution Neural Face Swapping for Visual Effects We propose an algorithm for fully automatic neural face swapping in images and videos. June 29, 2020Eurographics Symposium on Rendering (2020) Authors Jacek Naruniec (DisneyResearch|Studios) Leonhard...
by Martina Megaro | Jun 16, 2020 | Capture, Machine Learning, VFX
Attention-Driven Cropping for Very High Resolution Facial Landmark Detection Facial landmark detection is a fundamental task for many consumer and high-end applications and is almost entirely solved by machine learning methods today. June 16, 2020IEEE Conference on...
by Martina Megaro | May 25, 2020 | Capture, Machine Learning, VFX
Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems We introduce a novel iterative solver for nonlinear least squares optimization of large-scale semi-sparse problems. May 25, 2020Eurographics 2020 Authors Marco Fratarcangeli...
by Martina Megaro | May 25, 2020 | Capture, Machine Learning, VFX
Facial Expression Synthesis using a Global-Local Multilinear Framework We present a practical method to synthesize plausible 3D facial expressions that preserve the identity of a target subject. May 25, 2020Eurographics 2020 Authors Mengjiao Wang...
by Martina Megaro | Nov 4, 2019 | Video Processing, Visual Computing
Deep Generative Video Compression We propose an end-to-end, deep probabilistic modeling approach to compress low-resolution videos. Our approach builds upon variational autoencoder (VAE) models for sequential data and combines them with recent work on neural image...
