Mobile QR Code QR CODE

2025

Reject Ratio

81.5%

References

1 
Saharia C. , Chan W. , Saxena S. , 2022, Photorealistic text-to-image diffusion models with deep language understanding, Advances in Neural Information Processing Systems, Vol. 35, pp. 36479-36494DOI
2 
Blattmann R. Rombach A. , Lorenz D. , Esser P. , Ommer B. , 2022, High-resolution image synthesis with latent diffusion models, pp. 10674-10685DOI
3 
Betker J. , Goh G. , Jing L. , Brooks T. , Wang J. , Li L. , Zhung L. Ouyang J. , Lee J. , Guo Y. , Manassra W. , Dhariwal P. , Chu C. , Jiao Y. , 2023, Improving image generation with better captionsGoogle Search
4 
Ramesh A. , Dhariwai P. , Nichol A. , Chu C. , Chen M. , 2022, Hierarchical text-conditional image generation with CLIP latents, arXiv preprint arXiv:2204.06125DOI
5 
Brade S. , Wang B. , Sousa M. , Oore S. , Grossman T. , 2023, Promptify: Text-to-image generation through interactive prompt exploration with large language modelsDOI
6 
Hao Y. , Chi Z. , Dong L. , Wei F. , 2024, Optimizing prompts for text-to-image generation, Advances in Neural Information Processing Systems, Vol. 36DOI
7 
Krizhevsky A. , Hinton G. , 2009, Learning multiple layers of features from tiny imagesGoogle Search
8 
Xiao H. , Rasul K. , Vollgraf R. , 2017, Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms, arXiv preprint arXiv:1708.07747DOI
9 
Deng J. , Dong W. , Socher R. , Li L.-J. , Li K. , Li F.-F. , 2009, ImageNet: A large-scale hierarchical image databaseDOI
10 
Lin T.-Y. , Maire M. , Belongie S. , Hays J. , Perona P. , Ramanan D. , Dollár P. , Zitnick C. K. , 2014, Microsoft COCO: Common objects in context, Vol. 13, pp. 740-755DOI
11 
Torralba A. , Fergus R. , Freeman W. T. , 2008, 80 million tiny images: A large data set for nonparametric object and scene recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, No. 11, pp. 1958-1970DOI
12 
Wang Z. , Bao J. , Zhou W. , Wnag W. , Hu H. , Chen H. , Li H. , 2023, Dire for diffusion-generated image detectionDOI
13 
Zhu M. , Chen H. , Yan Q. , Huang X. , Lin G. , Li W. , Tu Z. , Hu H. , Hu J. , Wang Y. , 2024, GenImage: A million-scale benchmark for detecting AI-generated image, Advances in Neural Information Processing Systems, Vol. 36DOI
14 
Gu S. , Bao J. , Chen D. , Wen F. , 2020, GIQA: Generated image quality assessment, pp. 369-385DOI
15 
Radford A. , Kim J. W. , Hallacy C. , Ramesh A. , Goh G. , Agarwal S. , Sastry G. , Askell A. , Mishkin P. , Clark J. , Krueger G. , Sutskever I. , 2021, Learning transferable visual models from natural language supervisionDOI
16 
Zamir S. W. , Arora A. , Khan S. , Hayat M. , Khan F. S. , Yang M.-H. , 2022, Restormer: Efficient transformer for high-resolution image restorationDOI
17 
Achiam J. , Adler S. , 2023, GPT-4 technical report, arXiv preprint arXiv:2303.08774DOI
18 
Jocher G. , 2023, Ultralytics YOLO (Version 8.0.0) [Computer software]Google Search
19 
Kang D. , Hong J. , Kim J. , Song M. , Kim D. , Park S. , 2022, A case study of object detection via generated image using deep learning model based on image generation, pp. 203-206Google Search