I have published many examples of Neural Nets in Maya using Python. Here is how to implement them in C++ In the past year, I have discussed many neural net types and their applications here in the blog. I have implemented simplified examples of most of them using the Maya …
In this article, you’ll learn how to train a convolutional neural network to generate normal maps from color images. Convolutional neural networks are great at dealing with images, as well as other types of structured data. If you want to understand how they work, please read this other article first. …
Networks built out of one or many convolutional layers are the standard in image classification and are also used for other types of structured data. Understand how they work! Convolutional neural network layers are readily available in frameworks such as Tensorflow, Theano, CNTK, and others. You don’t need to learn …
In this article, you’ll learn how to train an autoencoding Neural Network to compress and denoise motion capture data and display it inside Maya Autoencoders are at the heart of some raytracer denoising and image upscaling (aka. super-resolution) technologies. Despite the pompous name, an autoencoder is just a Neural Network …
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 …
DeepMimic relies on reinforcement learning to teach skills to ragdolls. It’s time for you to experiment with a simplified version of it in Maya. In previous posts, we have discussed the approximation of character animation with Neural Networks. This approximation was kinematic, that is, it was not concerned with the …
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 …
In the second installment of the SIGGRAPH Series, I have shown you how the MANN model works. Now it is time to download and understand the repo provided by the authors. Controlling characters in real time demands a system to blend their movements according to the user’s input. Historically this …
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 …
