By
Bharath K
GAN
By
Bharath K
Understanding GauGAN Part 4: Debugging Training & Deciding If GauGAN Is Right For You
In this post we cover how to tackle common training issues that may arise with GauGAN. We conclude with advice on whether GauGAN will fit your business needs or not.
4 years ago
Understanding GauGAN Part 3: Model Evaluation Techniques
In Part 3 of the GauGAN series we cover how to evaluate model performance, and how GauGAN compares to models like Pix2PixHD, SIMS, and CRN.
4 years ago
Understanding GauGAN Part 2: Training on Custom Datasets
In this article we cover how to train GauGAN on your own custom dataset. This is part of a series on Nvidia GauGANs.
4 years ago
Understanding GauGAN Part 1: Unraveling Nvidia's Landscape Painting GANs
In this article we explain what GauGANs are, and how their architecture and objective functions work. This is part of a series on Nvidia GauGANs.
4 years ago
Implementing CycleGAN for Age Conversion
In this tutorial we'll train CycleGAN with Keras to generate images which age a subject's face, either forwards or backwards.
4 years ago
DeepFake Faceoff w/ Dr. Fakenstein & CtrlShiftFace
Deepfake technology is unlocking a new era of media production. As with all technologies, both positive and harmful use cases exist. As ethical technologists, we aspire to push the limits of what is possible, while minding the impact of the tools we create.
By
John
Unpaired Image to Image Translation with CycleGAN
This article gives insights into the working mechanism of a Generative Adversarial Network and one of its popular variants, the Cycle Consistent Adversarial Network.
5 years ago
Building a simple Generative Adversarial Network (GAN) using TensorFlow
Generative Adversarial Networks or GANs are one of the most active areas in deep learning research and development due to their incredible ability to generate synthetic results. In this blog, we will build out the basic intuition of GANs through a concrete example.
By
Aadil Hayat
