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TheKernel01/
DeForge-AIGIBench-Models

Name: DeForge-AIGIBench-Models
Availability: InStock

HorizonTEL/AIGIBench

2501.15253

cc-by-nc-sa-4.0

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Is Artificial Intelligence Generated Image Detection a Solved Problem?

Ziqiang Li¹, Jiazhen Yan¹, Ziwen He¹, Kai Zeng², Weiwei Jiang¹, Lizhi Xiong¹, Zhangjie Fu^1‡

^‡Corresponding author

¹Nanjing University of Information Science and Technology ²University of Siena

This repository is the official pre-trained checkpoints of the AIGIBench in Setting-II: Training on 144K images generated by both SD-v1.4 and ProGAN, covering the same four object categories.

Of course, if you need the code from the original paper, the following is the corresponding detection code in the paper：

ResNet-50: Deep Residual Learning for Image Recognition
CNNDetection: CNN-generated images are surprisingly easy to spot...for now
GramNet: Global Texture Enhancement for Fake Face Detection in the Wild
LGrad: Learning on Gradients: Generalized Artifacts Representation for GAN-Generated Images Detection
CLIPDetection: Towards Universal Fake Image Detectors that Generalize Across Generative Models
FreqNet: FreqNet: A Frequency-domain Image Super-Resolution Network with Dicrete Cosine Transform
NPR: Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection
DFFreq: Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection
LaDeDa: Real-Time Deepfake Detection in the Real-World
AIDE: A Sanity Check for AI-generated Image Detection
SAFE: Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspectives

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TheKernel01/DeForge-AIGIBench-Models

Is Artificial Intelligence Generated Image Detection a Solved Problem?

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TheKernel01/
DeForge-AIGIBench-Models