by Martina Megaro | May 3, 2021 | Video Processing, Visual Computing
Robust Image Denoising using Kernel Predicting Networks We present a new method for designing high quality denoisers that are robust to varying noise characteristics of input images. May 3, 2021Eurographics 2021 Authors Zhilin Cai (DisneyResearch|Studios/ETH...
by Martina Megaro | May 3, 2021 | Video Processing, Visual Computing
Deep HDR estimation with generative detail reconstruction We present qualitative and quantitative comparisons with existing techniques where our method achieves state-of-the-art performance. May 3, 2021Eurographics 2021 Authors Yang Zhang...
by Martina Megaro | Nov 25, 2020 | Capture, Machine Learning, VFX
Semantic Deep Face Models We present a method for nonlinear 3D face modeling using neural architectures. November 25, 20203D International Conference on 3D Vision (3DV) (2020) Authors Prashanth Chandran (DisneyResearch|Studios/ETH Joint PhD) Derek Bradley...
by Martina Megaro | Nov 10, 2020 | Video Processing, Visual Computing
Deep Deinterlacing We propose a novel approach to deep video deinterlacing. November 10, 2020SMPTE Annual Technical Conference & Exhibition (2020) Authors Michael Bernasconi (DisneyResearch|Studios) Abdelaziz Djelouah (DisneyResearch|Studios) Sally...
by Martina Megaro | Aug 17, 2020 | Capture, Machine Learning, VFX
Data-driven Extraction and Composition of Secondary Dynamics in Facial Performance Capture Our work aims to compute and characterize the difference between the captured dynamic facial performance, and a speculative quasistatic variant of the same motion should the...
