A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt

Y Cao, S Li, Y Liu, Z Yan, Y Dai, PS Yu… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

Diffusion models in vision: A survey

FA Croitoru, V Hondru, RT Ionescu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Denoising diffusion models represent a recent emerging topic in computer vision,
demonstrating remarkable results in the area of generative modeling. A diffusion model is a …

Structure and content-guided video synthesis with diffusion models

P Esser, J Chiu, P Atighehchian… - Proceedings of the …, 2023 - openaccess.thecvf.com
Text-guided generative diffusion models unlock powerful image creation and editing tools.
Recent approaches that edit the content of footage while retaining structure require …

Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

C Lu, Y Zhou, F Bao, J Chen, C Li… - Advances in Neural …, 2022 - proceedings.neurips.cc
Diffusion probabilistic models (DPMs) are emerging powerful generative models. Despite
their high-quality generation performance, DPMs still suffer from their slow sampling as they …

Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models

C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu - arXiv preprint arXiv:2211.01095, 2022 - arxiv.org
Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution
image synthesis, especially in recent large-scale text-to-image generation applications. An …

A survey on generative diffusion models

H Cao, C Tan, Z Gao, Y Xu, G Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep generative models have unlocked another profound realm of human creativity. By
capturing and generalizing patterns within data, we have entered the epoch of all …

High-resolution image synthesis with latent diffusion models

R Rombach, A Blattmann, D Lorenz… - Proceedings of the …, 2022 - openaccess.thecvf.com
By decomposing the image formation process into a sequential application of denoising
autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image …

Versatile diffusion: Text, images and variations all in one diffusion model

X Xu, Z Wang, G Zhang, K Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Recent advances in diffusion models have set an impressive milestone in many generation
tasks, and trending works such as DALL-E2, Imagen, and Stable Diffusion have attracted …

Tackling the generative learning trilemma with denoising diffusion gans

Z Xiao, K Kreis, A Vahdat - arXiv preprint arXiv:2112.07804, 2021 - arxiv.org
A wide variety of deep generative models has been developed in the past decade. Yet,
these models often struggle with simultaneously addressing three key requirements …

Score-based generative modeling in latent space

A Vahdat, K Kreis, J Kautz - Advances in neural information …, 2021 - proceedings.neurips.cc
Score-based generative models (SGMs) have recently demonstrated impressive results in
terms of both sample quality and distribution coverage. However, they are usually applied …