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Most recent style-transfer techniques based on generative architectures are able to obtain synthetic multimedia contents, or commonly called deepfakes, with almost no artifacts. Researchers already demonstrated that synthetic images contain…

Computer Vision and Pattern Recognition · Computer Science 2022-06-08 Luca Guarnera , Oliver Giudice , Sebastiano Battiato

Currently, high-fidelity text-to-image models are developed in an accelerating pace. Among them, Diffusion Models have led to a remarkable improvement in the quality of image generation, making it vary challenging to distinguish between…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziyue Zeng , Haoyuan Liu , Dingjie Peng , Luoxu Jing , Hiroshi Watanabe

In recent years, diffusion models have become one of the main methods for generating images. However, detecting images generated by these models remains a challenging task. This paper proposes a novel method for detecting images generated…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Dmitry Vesnin , Dmitry Levshun , Andrey Chechulin

Robust invisible watermarks are widely used to support copyright protection, content provenance, and accountability by embedding hidden signals designed to survive common post-processing operations. However, diffusion-based image editing…

Image and Video Processing · Electrical Eng. & Systems 2026-03-16 Qian Qi , Jiangyun Tang , Jim Lee , Emily Davis , Finn Carter

Driven by the new generation of multi-modal large models, such as Stable Diffusion (SD), image manipulation technologies have advanced rapidly, posing significant challenges to image forensics. However, existing image forgery localization…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Yang Su , Shunquan Tan , Jiwu Huang

Detecting fake images is becoming a major goal of computer vision. This need is becoming more and more pressing with the continuous improvement of synthesis methods based on Generative Adversarial Networks (GAN), and even more with the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-30 Riccardo Corvi , Davide Cozzolino , Giovanni Poggi , Koki Nagano , Luisa Verdoliva

The recent computer graphics developments have upraised the quality of the generated digital content, astonishing the most skeptical viewer. Games and movies have taken advantage of this fact but, at the same time, these advances have…

Computer Vision and Pattern Recognition · Computer Science 2017-11-29 Edmar R. S. de Rezende , Guilherme C. S. Ruppert , Antonio Theophilo , Tiago Carvalho

Latent generative models (e.g., Stable Diffusion) have become more and more popular, but concerns have arisen regarding potential misuse related to images generated by these models. It is, therefore, necessary to analyze the origin of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Zhenting Wang , Vikash Sehwag , Chen Chen , Lingjuan Lyu , Dimitris N. Metaxas , Shiqing Ma

We generate synthetic images with the "Stable Diffusion" image generation model using the Wordnet taxonomy and the definitions of concepts it contains. This synthetic image database can be used as training data for data augmentation in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Andreas Stöckl

The evolution of artificial intelligence (AI) has catalyzed a transformation in digital content generation, with profound implications for cyber influence operations. This report delves into the potential and limitations of generative deep…

Computers and Society · Computer Science 2024-03-20 Melanie Mathys , Marco Willi , Michael Graber , Raphael Meier

Recently, the progress of learning-by-synthesis has proposed a training model for synthetic images, which can effectively reduce the cost of human and material resources. However, due to the different distribution of synthetic images…

Computer Vision and Pattern Recognition · Computer Science 2019-03-15 Tongtong Zhao , Yuxiao Yan , Ibrahim Shehi Shehu , Xianping Fu , Huibing Wang

Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obtaining accurate human annotations is labor-intensive and…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Ling Fu , Zijie Wu , Yingying Zhu , Yuliang Liu , Xiang Bai

Text-to-image diffusion models have revolutionized image synthesis and editing, but precise control over stylistic attributes remains a challenge, often causing unintended content modifications. We propose an approach for fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Max Reimann , Benito Buchheim , Jürgen Döllner

The rapid progress of Deepfake technology has made face swapping highly realistic, raising concerns about the malicious use of fabricated facial content. Existing methods often struggle to generalize to unseen domains due to the diverse…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Ke Sun , Shen Chen , Taiping Yao , Hong Liu , Xiaoshuai Sun , Shouhong Ding , Rongrong Ji

Building generic robotic manipulation systems often requires large amounts of real-world data, which can be dificult to collect. Synthetic data generation offers a promising alternative, but limiting the sim-to-real gap requires significant…

Robotics · Computer Science 2024-11-18 Thomas Lips , Francis wyffels

Stable Diffusion has established itself as a foundation model in generative AI artistic applications, receiving widespread research and application. Some recent fine-tuning methods have made it feasible for individuals to implant…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Zhengyue Zhao , Jinhao Duan , Kaidi Xu , Chenan Wang , Rui Zhang , Zidong Du , Qi Guo , Xing Hu

Anomaly detection plays a vital role in industrial manufacturing. Due to the scarcity of real defect images, unsupervised approaches that rely solely on normal images have been extensively studied. Recently, diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Sungho Kang , Hyunkyu Park , Yeonho Lee , Hanbyul Lee , Mijoo Jeong , YeongHyeon Park , Injae Lee , Juneho Yi

Recent progress in text-to-image (TTI) systems, such as StableDiffusion, Imagen, and DALL-E 2, have made it possible to create realistic images with simple text prompts. It is tempting to use these systems to eliminate the manual task of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 David Marwood , Shumeet Baluja , Yair Alon

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 data and beyond. Additionally, their formulation allows for a…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Robin Rombach , Andreas Blattmann , Dominik Lorenz , Patrick Esser , Björn Ommer

The recent proliferation of fake portrait videos poses direct threats on society, law, and privacy. Believing the fake video of a politician, distributing fake pornographic content of celebrities, fabricating impersonated fake videos as…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Umur Aybars Ciftci , Ilke Demir