In this latest SIGGRAPH, Deep Learning was a hot topic. Many papers relied on it, some sessions were all about it. Dmytro Korolov, an experienced Pipeline Technical Director working at MPC, moderated a panel on the topic alongside Doug Roble (Digital Domain), Rob Pieke (MPC), Renaldas Zioma (Unity), Jeff Kember …
This is the third installment of the 3DeepLearner 2018 SIGGRAPH Series where I cover the most interesting deep learning papers (according to our audience) in a short video format. This video covers DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills by Peng et al. Link to the paper: https://xbpeng.github.io/projects/DeepMimic/index.html …
The second installment in the SIGGRAPH series is here. The ‘Mode-Adaptive Neural Networks for Quadruped Motion Control‘ by Zhang, Stark, et al. was the most voted paper in our pool. So I think you’ll like this. I’ve also created a guide to the authors’ GitHub repository, check it out! Links …
The SIGGRAPH series is here. You have cast your votes, now I’m publishing four short videos (and support material) on the papers you have found most interesting. I’ll publish this videos bi-weekly. The first one is on the paper ‘Fast and Deep Deformation Approximations’ by Bailey et al. Hope you …
In the first installment of the SIGGRAPH Series, I have shown you how the FDDA model works. Now it is time for you to implement it yourself in Maya. 3D animated characters in feature films use sophisticated rigs with complex deformations that can be computationally intensive. The authors of the …
