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The tremendous recent advances in generative artificial intelligence techniques have led to significant successes and promise in a wide range of different applications ranging from conversational agents and textual content generation to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Hossein Aboutalebi , Dayou Mao , Rongqi Fan , Carol Xu , Chris He , Alexander Wong

The recent breakthroughs in OpenAI's GPT4o model have demonstrated surprisingly good capabilities in image generation and editing, resulting in significant excitement in the community. This technical report presents the first-look…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Zhiyuan Yan , Junyan Ye , Weijia Li , Zilong Huang , Shenghai Yuan , Xiangyang He , Kaiqing Lin , Jun He , Conghui He , Li Yuan

OpenAI's multimodal GPT-4o has demonstrated remarkable capabilities in image generation and editing, yet its ability to achieve world knowledge-informed semantic synthesis--seamlessly integrating domain knowledge, contextual reasoning, and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Ning Li , Jingran Zhang , Justin Cui

The landscape of image generation has rapidly evolved, from early GAN-based approaches to diffusion models and, most recently, to unified generative architectures that seek to bridge understanding and generation tasks. Recent advances,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Sixiang Chen , Jinbin Bai , Zhuoran Zhao , Tian Ye , Qingyu Shi , Donghao Zhou , Wenhao Chai , Xin Lin , Jianzong Wu , Chao Tang , Shilin Xu , Tao Zhang , Haobo Yuan , Yikang Zhou , Wei Chow , Linfeng Li , Xiangtai Li , Lei Zhu , Lu Qi

Recently, GPT-4o has garnered significant attention for its strong performance in image generation, yet open-source models still lag behind. Several studies have explored distilling image data from GPT-4o to enhance open-source models,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Junyan Ye , Dongzhi Jiang , Zihao Wang , Leqi Zhu , Zhenghao Hu , Zilong Huang , Jun He , Zhiyuan Yan , Jinghua Yu , Hongsheng Li , Conghui He , Weijia Li

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 performance of unified multimodal models for image generation and editing is fundamentally constrained by the quality and comprehensiveness of their training data. While existing datasets have covered basic tasks like style transfer and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Zhihong Chen , Xuehai Bai , Yang Shi , Chaoyou Fu , Huanyu Zhang , Haotian Wang , Xiaoyan Sun , Zhang Zhang , Liang Wang , Yuanxing Zhang , Pengfei Wan , Yi-Fan Zhang

Recent advances in OpenAI's GPT-series multimodal generation models have shown remarkable capabilities in producing visually compelling images. In this work, we investigate its potential impact on the image restoration community. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Hao Yang , Yan Yang , Ruikun Zhang , Liyuan Pan

Context: This paper provides an in-depth examination of the generation and evaluation of Metamorphic Relations (MRs) using GPT models developed by OpenAI, with a particular focus on the capabilities of GPT-4 in software testing…

Software Engineering · Computer Science 2025-03-31 Yifan Zhang , Dave Towey , Matthew Pike , Quang-Hung Luu , Huai Liu , Tsong Yueh Chen

In the burgeoning field of AI-driven image generation, the quest for precision and relevance in response to textual prompts remains paramount. This paper introduces GPTDrawer, an innovative pipeline that leverages the generative prowess of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Kun Li , Xinwei Chen , Tianyou Song , Hansong Zhang , Wenzhe Zhang , Qing Shan

The rapid advancement of generative models, such as GANs and Diffusion models, has enabled the creation of highly realistic synthetic images, raising serious concerns about misinformation, deepfakes, and copyright infringement. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Ziqiang Li , Jiazhen Yan , Ziwen He , Kai Zeng , Weiwei Jiang , Lizhi Xiong , Zhangjie Fu

Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in their capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remains…

Ultra-high-resolution image synthesis holds significant potential, yet remains an underexplored challenge due to the absence of standardized benchmarks and computational constraints. In this paper, we establish Aesthetic-4K, a meticulously…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Jinjin Zhang , Qiuyu Huang , Junjie Liu , Xiefan Guo , Di Huang

The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity. We present Ai-GenBench, a novel benchmark designed to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Lorenzo Pellegrini , Davide Cozzolino , Serafino Pandolfini , Davide Maltoni , Matteo Ferrara , Luisa Verdoliva , Marco Prati , Marco Ramilli

As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With such overwhelming media coverage, it is almost impossible for…

With the rapid development of deep generative models (such as Generative Adversarial Networks and Diffusion models), AI-synthesized images are now of such high quality that humans can hardly distinguish them from pristine ones. Although…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yan Ju , Shan Jia , Jialing Cai , Haiying Guan , Siwei Lyu

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

Recently, the visual generation ability by GPT-4o(mni) has been unlocked by OpenAI. It demonstrates a very remarkable generation capability with excellent multimodal condition understanding and varied task instructions. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Pu Cao , Feng Zhou , Junyi Ji , Qingye Kong , Zhixiang Lv , Mingjian Zhang , Xuekun Zhao , Siqi Wu , Yinghui Lin , Qing Song , Lu Yang

Generative AI based on foundation models provides a first glimpse into the world represented by machines trained on vast amounts of multimodal data ingested by these models during training. If we consider the resulting models as knowledge…

Computers and Society · Computer Science 2024-04-12 Zilong Liu , Krzysztof Janowicz , Kitty Currier , Meilin Shi

Modern multimodal generators can now produce scientific figures at near-publishable quality, creating a new challenge for visual forensics and research integrity. Unlike conventional AI-generated natural images, scientific figures are…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 You Hu , Chenzhuo Zhao , Changfa Mo , Haotian Liu , Xiaobai Li
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