SEED Detector

This repository contains the official detector model for SEED, presented in the paper SEED: Simple ViT and Evolving Harness for Explainable Text Forgery Detection.

SEED Detector is a lightweight vision transformer model for document forgery detection. It localizes tampered regions in document images and classifies images as real or forged.

Architecture

Usage

Repository: GitHub | Checkpoint: Jason37437/SEED / Google Drive

from model.hf_wrapper import EoMTForTamperingDetection

model = EoMTForTamperingDetection.from_pretrained("Jason37437/SEED")
model.eval()

# The model outputs:
#   - mask_logits: per-query segmentation masks
#   - class_logits: per-query foreground/background scores  
#   - image_logits: image-level real vs forged classification

Performance

Localization (pixel-level F1)

Detection (image-level F1)

Citation

@article{wong2026seed,
  title={SEED: Simple ViT and Evolving Harness for Explainable Text Forgery Detection},
  author={Wong, Kahim and others},
  journal={arXiv preprint arXiv:2606.21138},
  year={2026}
}

License

MIT License.