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 …

Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review

Y Lu, D Chen, E Olaniyi, Y Huang - Computers and Electronics in …, 2022 - Elsevier
In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

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 …

Diffuseq: Sequence to sequence text generation with diffusion models

S Gong, M Li, J Feng, Z Wu, LP Kong - arXiv preprint arXiv:2210.08933, 2022 - arxiv.org
Recently, diffusion models have emerged as a new paradigm for generative models.
Despite the success in domains using continuous signals such as vision and audio …

Palette: Image-to-image diffusion models

C Saharia, W Chan, H Chang, C Lee, J Ho… - ACM SIGGRAPH 2022 …, 2022 - dl.acm.org
This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

Forget-me-not: Learning to forget in text-to-image diffusion models

G Zhang, K Wang, X Xu, Z Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
The significant advances in applications of text-to-image generation models have prompted
the demand of a post-hoc adaptation algorithms that can efficiently remove unwanted …

Image super-resolution via iterative refinement

C Saharia, J Ho, W Chan, T Salimans… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
We present SR3, an approach to image Super-Resolution via Repeated Refinement. SR3
adapts denoising diffusion probabilistic models (Ho et al. 2020),(Sohl-Dickstein et al. 2015) …

Deep learning for anomaly detection: A review

G Pang, C Shen, L Cao, AVD Hengel - ACM computing surveys (CSUR), 2021 - dl.acm.org
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …

Retrieval-augmented diffusion models

A Blattmann, R Rombach, K Oktay… - Advances in Neural …, 2022 - proceedings.neurips.cc
Novel architectures have recently improved generative image synthesis leading to excellent
visual quality in various tasks. Much of this success is due to the scalability of these …

Theseus: A library for differentiable nonlinear optimization

L Pineda, T Fan, M Monge… - Advances in …, 2022 - proceedings.neurips.cc
We present Theseus, an efficient application-agnostic open source library for differentiable
nonlinear least squares (DNLS) optimization built on PyTorch, providing a common …