aaronkantrowitz/ai-human-generated-image-detection

CapCheck AI vs Human-Generated Image Detection

Vision Transformer (ViT) fine-tuned for detecting AI-generated images. Uses newer training data than the original CIFAKE-based model.

Model Lineage & Attribution

This model builds on the work of others:

Special thanks to:

• —Google for the Vision Transformer (ViT) architecture
• —dima806 for fine-tuning on AI vs human-generated image datasets

Model Description

• —Architecture: ViT-Base (86M parameters)
• —Input Size: 224x224 pixels
• —Training Data: AI-generated vs human-created images (newer dataset than CIFAKE)
• —Task: Binary classification (human vs AI-generated)

Usage

from transformers import pipeline

detector = pipeline("image-classification", model="capcheck/ai-human-generated-image-detection")
result = detector("path/to/image.jpg")

# Output:
# [{"label": "AI-generated", "score": 0.95}, {"label": "human", "score": 0.05}]

Labels

Comparison with capcheck/ai-image-detection

Limitations

• —May have reduced accuracy on very new AI generators not in training data
• —Heavily compressed images (low JPEG quality) can affect results
• —Works best on images with clear subjects (224x224+ pixels)

Intended Use

• —Content moderation and authenticity verification
• —Research into AI-generated content detection
• —Educational purposes

Not intended for:

• —Making consequential decisions without human review
• —Law enforcement evidence without corroborating sources

License

Apache 2.0 (inherited from Google ViT and dima806's fine-tuned model)

Citation

@misc{capcheck-ai-human-generated-detection,
  author = {CapCheck},
  title = {AI vs Human-Generated Image Detection Model},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/capcheck/ai-human-generated-image-detection},
  note = {Based on dima806/ai_vs_human_generated_image_detection, fine-tuned from google/vit-base-patch16-224-in21k}
}