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Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from real ones. AI-generated images may lead to ubiquitous…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Nan Zhong , Yiran Xu , Sheng Li , Zhenxing Qian , Xinpeng Zhang

The increasing difficulty in accurately detecting forged images generated by AIGC(Artificial Intelligence Generative Content) poses many risks, necessitating the development of effective methods to identify and further locate forged areas.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Yang Liu , Xiaofei Li , Jun Zhang , Shengze Hu , Jun Lei

As AI-generated image (AIGI) methods become more powerful and accessible, it has become a critical task to determine if an image is real or AI-generated. Because AIGI lack the signatures of photographs and have their own unique patterns,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 A. G. Moskowitz , T. Gaona , J. Peterson

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 are seeking to uncover the background and secrets behind its…

Artificial Intelligence · Computer Science 2023-03-09 Yihan Cao , Siyu Li , Yixin Liu , Zhiling Yan , Yutong Dai , Philip S. Yu , Lichao Sun

With growing abilities of generative models, artificial content detection becomes an increasingly important and difficult task. However, all popular approaches to this problem suffer from poor generalization across domains and generative…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Tatiana Gaintseva , Laida Kushnareva , German Magai , Irina Piontkovskaya , Sergey Nikolenko , Martin Benning , Serguei Barannikov , Gregory Slabaugh

Rapid advancement in generative AI and large language models (LLMs) has enabled the generation of highly realistic and contextually relevant digital content. LLMs such as ChatGPT with DALL-E integration and Stable Diffusion techniques can…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Jitendra Sharma , Arthur Carvalho , Suman Bhunia

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the…

Artificial Intelligence · Computer Science 2023-01-10 Hongyang Du , Zonghang Li , Dusit Niyato , Jiawen Kang , Zehui Xiong , Xuemin , Shen , Dong In Kim

AI-generated content (AIGC) methods aim to produce text, images, videos, 3D assets, and other media using AI algorithms. Due to its wide range of applications and the potential of recent works, AIGC developments -- especially in Machine…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Lin Geng Foo , Hossein Rahmani , Jun Liu

New advancements for the detection of synthetic images are critical for fighting disinformation, as the capabilities of generative AI models continuously evolve and can lead to hyper-realistic synthetic imagery at unprecedented scale and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Pantelis Dogoulis , Giorgos Kordopatis-Zilos , Ioannis Kompatsiaris , Symeon Papadopoulos

Artificial Intelligence Generated Content (AIGC) has rapidly emerged with the capability to generate different forms of content, including text, images, videos, and other modalities, which can achieve a quality similar to content created by…

The rapid advancement in generative AI models has enabled the creation of photorealistic images. At the same time, there are growing concerns about the potential misuse and dangers of generated content, as well as a pressing need for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Zhenhan Huang , Pin-Yu Chen , Tejaswini Pedapati , Jianxi Gao

Recent advances in Generative AI (GenAI) have led to significant improvements in the quality of generated visual content. As AI-generated visual content becomes increasingly indistinguishable from real content, the challenge of detecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Keerthi Veeramachaneni , Praveen Tirupattur , Amrit Singh Bedi , Mubarak Shah

Distinguishing between computer-generated (CG) and natural photographic (PG) images is of great importance to verify the authenticity and originality of digital images. However, the recent cutting-edge generation methods enable high…

Computer Vision and Pattern Recognition · Computer Science 2022-09-08 Qiang Xu , Shan Jia , Xinghao Jiang , Tanfeng Sun , Zhe Wang , Hong Yan

While the technology for detecting AI-Generated Content (AIGC) images has advanced rapidly, the field still faces two core issues: poor reproducibility and insufficient gen eralizability, which hinder the practical application of such…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Yihang Duan

With the advancement of generation models, AI-generated content (AIGC) is becoming more realistic, flooding the Internet. A recent study suggests that this phenomenon causes source bias in text retrieval for web search. Specifically, neural…

Information Retrieval · Computer Science 2024-05-28 Shicheng Xu , Danyang Hou , Liang Pang , Jingcheng Deng , Jun Xu , Huawei Shen , Xueqi Cheng

With the rapid advancement of AI generative models, the visual quality of AI-generated images (AIIs) has become increasingly close to natural images, which inevitably raises security concerns. Most AII detectors often employ the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Zhipeng Yuan , Kai Wang , Weize Quan , Dong-Ming Yan , Tieru Wu

Artificial Intelligence Generated Content (AIGC) assisting image production triggers controversy in journalism while attracting attention from media agencies. Key issues involve misinformation, authenticity, semantic fidelity, and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Yajie Yang , Yuqing Zhao , Xiaochao Xi , Yinan Zhu

\underline{AI} \underline{G}enerated \underline{C}ontent (\textbf{AIGC}) has gained widespread attention with the increasing efficiency of deep learning in content creation. AIGC, created with the assistance of artificial intelligence…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Zicheng Zhang , Chunyi Li , Wei Sun , Xiaohong Liu , Xiongkuo Min , Guangtao Zhai

State-of-the-art methods in image-to-image translation are capable of learning a mapping from a source domain to a target domain with unpaired image data. Though the existing methods have achieved promising results, they still produce…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Hao Tang , Hong Liu , Dan Xu , Philip H. S. Torr , Nicu Sebe

The rapid development of generative AI has made AI-generated images increasingly realistic and high-resolution. Most AI-generated image detection architectures typically downsample images before inputting them into models, risking the loss…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Lawrence Han
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