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Improved Techniques for Training GANs
The dataset used in the paper is a GAN training dataset. -
Text-to-Image Synthesis
The dataset used in the paper is a text-to-image synthesis dataset. -
LatentGAN Autoencoder: Learning Disentangled Latent Distribution
LatentGAN Autoencoder: Learning Disentangled Latent Distribution -
Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation
Conditional image generation using denoising diffusion probabilistic model with entropy-driven sampling and training scheme -
ODIN: On-demand Data Formulation to Mitigate Dataset Lock-in
ODIN is an innovative approach that addresses the problem of dataset constraints by integrating generative AI models. -
Directly Denosing Diffusion Models
Directly Denoising Diffusion Models: a simple and generic approach for generating realistic images with few-step sampling, while multistep sampling is still preserved for better... -
SD-DiT: Unleashing the Power of Self-supervised Discrimination in Diffusion T...
Diffusion Transformer (DiT) has emerged as the new trend of generative diffusion models on image generation. In view of extremely slow convergence in typical DiT, recent... -
Stable Diffusion safety filter dataset
The dataset used in the paper is the Stable Diffusion safety filter dataset, which contains images that are generated using the Stable Diffusion model and are classified as safe... -
CelebA-HQ-FI and CelebA-25000
The dataset used in the paper is the CelebA-HQ-FI and CelebA-25000 datasets. -
Style Aligned Image Generation
StyleAligned is a method for generating style-consistent images using a reference style image. -
Generative Adversarial Networks
Generative Adversarial Networks (GANs) consist of two networks: a generator G(z) and a discriminator D(x). The discriminator is trying to distinguish real objects from objects... -
Photorealistic text-to-image diffusion models with deep language understanding
The authors present a photorealistic text-to-image diffusion model with deep language understanding. -
SynthBuster dataset
The SynthBuster dataset is a collection of images generated by various diffusion models. -
SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTA
Learning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream tasks. The proposed method learns sparse data... -
CIFAR10 and CelebA Datasets
The dataset used in the paper is the CIFAR10 and CelebA datasets.
