This is a script to generate new images of human faces using the technique of generative adversarial networks (GAN), as described in the paper byIan J. Goodfellow. GANs train two networks at the same time: A Generator (G) that draws/creates new images and a Discriminator (D) that disting...
This paper describes the architecture of a GAN model, which incorporates a combination of a generator model and a discriminator model, and the training procedure using Anime Face Dataset and CelebFaces Attributes Dataset available. The evaluation of the execution of the suggested GAN model is ...
• ImFace: A Nonlinear 3D Morphable Face Model with Implicit Neural Representations paper • COAP: Compositional Articulated Occupancy of People paper code • SunStage: Portrait Reconstruction and Relighting using the Sun as a Light Stage paper • LISA: Learning Implicit Shape and Appearance of...
Human Portrait->Encoder->High Dimensional Vector->PGGAN Generator + anime-specific-batch-norm->Anime Portrait As mentioned inthe Facebook paper, letting the human and anime portraits share the same network will help the network realize that: although they look a little bit different, both human ...
At each stage of the network, it uses a cGAN[7] to learn the intermediate sketch, whereas a U-net[8] is adopted as the generator and a Patch-GAN[7] is also adopted as the discriminator. Let PP denote an input face photo in the Ord-Sketch dataset, ZZ denote the initial random ...
Personalized 3D human avatars have aroused a great deal of interest because it is attractive to most people, particularly generation Z, to have the digital
A GAN, a class of machine-learning framework coined by researcher (and current Apple employee) Ian Goodfellow, uses a combative, tug-of-war approach to improve its generative outcomes. It consists of two neural networks: A “generator” and a “discriminator” which pass outputs between one an...
2023 05 09 StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator Latent GAN CVPR 2023 2024 02 27 EMO Latent Diffusion Model arXiv 2024 03 04 FaceChain-ImagineID: Freely Crafting High-Fidelity Diverse Talking Faces from Disentangled Audio Latent Diffusion Model CVPR...
The authors of the papers (Jin et al.2022; Wang et al.2022) argue that current multi-person methods using either two-stage top-down or bottom-up approaches face issues with redundant computations and high computational costs, resulting in inadequate efficiency for real-time processing. Jin et ...
The objective of the generator is to produce images such that the discriminator cannot distin- guish between the real images and the generated images, where the discriminator has been trained to distinguish real images from generated images. The objective function of a generative adversarial network ...