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...
by Martina Megaro | Nov 1, 2019 | Machine Learning, Visual Computing
Differentiable Surface Splatting for Point-based Geometry Processing We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for point clouds. November 1, 2019ACM SIGGRAPH Asia 2019 Authors Yifan Wang (ETH Zurich) Serena...
