How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015
Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · R. Huang
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Implementation of Sequence Generative Adversarial Nets with Policy Gradient
The main features of lantaoyu/seqgan are: Computer Vision Applications, Security and Privacy, Video and Sequence Generation.
Open-source alternatives to lantaoyu/seqgan include: aravindhm/deep-goggle — Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015. ayanc/rpgan — RP-GAN: Stable GAN Training with Random Projections. borealisai/bre-gan — Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W… carpedm20/simulated-unsupervised-tensorflow — TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training". chrischoy/3d-r2n2 — Single/multi view image(s) to voxel reconstruction using a recurrent neural network. akashgit/veegan — VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning.
