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Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems

Fast Nonlinear Least Squares Optimization of Large-Scale Semi-Sparse Problems

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...
Deep Generative Video Compression

Deep Generative Video Compression

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...
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation

Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation

by Martina Megaro | Jun 10, 2019 | Machine Learning

Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation   We propose a novel,polynomial-time approximation of Shapley values in deep neural networks. June 10, 2019International Conference on Machine Learning (ICML) 2019  ...
Generating Animations from Screenplays

Generating Animations from Screenplays

by Martina Megaro | Jun 1, 2019 | Animation, Story Technology, Visual Computing

Generating Animations from Screenplays   In this paper, we develop a text-to-animation system which is capable of handling complex sentences. June 1, 2019*SEM 2019   Authors Yeyao Zhang (Disney Research/ETH Joint M.Sc.) Eleftheria Tsipidi (Disney Research) Sasha...
Learning-based Sampling for Natural Image Matting

Learning-based Sampling for Natural Image Matting

by Martina Megaro | May 28, 2019 | Machine Learning, Video Processing, Visual Computing

Learning-based Sampling for Natural Image Matting   We present a new sampling-based natural matting tech- nique that utilizes a pair of novel sampling networks for estimating background and foreground colors of pixels in unknown image regions. June 16, 2019IEEE...
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