by Martina Megaro | Jul 12, 2019 | Capture, VFX, Visual Computing
Accurate Markerless Jaw Tracking for Facial Performance Capture We present the first method to accurately track the invisible jaw based solely on the visible skin surface, without the need for any markers or augmentation of the actor. July 12, 2019ACM Siggraph 2019...
by Martina Megaro | Jul 12, 2019 | Rendering, Visual Computing
Neural Importance Sampling We propose to use deep neural networks for generating samples in Monte Carlo integration. July 12, 2019ACM Siggraph 2019 Authors Thomas Müller (Disney Research/ETH Joint PhD) Brian McWilliams (Disney Research) Fabrice Rousselle...
by Martina Megaro | Jun 16, 2019 | Machine Learning, Video Processing, Visual Computing
Neural Sequential Phrase Grounding (SeqGROUND) We propose an end-to-end approach for phrase grounding in images. June 16, 2019IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 Authors Pelin Dogan (Disney Research/ETH Joint PhD) Leonid...
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 ...
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...
