3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator does. Otherwise, if the main discriminator dominates the generator, the mirror symmetry problem will still occur. In practice, progressive training is able to guarantee this. We have trained many times from scratch. Adding an auxiliary discriminator stably solves the mirror symmetry problem.

Features

  • Demo videos
  • Model interpolation (web demo)
  • Download the pre-trained checkpoints
  • Pre-trained checkpoints
  • 3D-aware GANs
  • Based on NeRF (arXiv)

Project Samples

Project Activity

See All Activity >

License

MIT License

Follow CIPS-3D

CIPS-3D Web Site

You Might Also Like
MongoDB Atlas runs apps anywhere Icon
MongoDB Atlas runs apps anywhere

Deploy in 115+ regions with the modern database for every enterprise.

MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of CIPS-3D!

Additional Project Details

Programming Language

Python

Related Categories

Python Generative Adversarial Networks (GAN), Python Generative AI

Registered

2023-03-21