SEED

--- base_model: facebook/dinov3-vitl16-pretrain-lvd1689m datasets: - DocTamperV1 - vankey/RealText-V2 - Jason37437/RealText-V2-Syn25k language: en library_name: pytorch license: mit metrics: - f1 pipeline_tag: image-segmentation tags: - document-forgery-detection - tampering-detection - image-manipulation - vision-transformer - lora --- # 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](https://huggingface.co/papers/2606.21138). **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 | Component | Detail | |-----------|--------| | Backbone | [DINOv3 ViT-L/16](https://huggingface.co/facebook/dinov3-vitl16-pretrain-lvd1689m) | | Finetuning | LoRA (rank=1, attention + MLP) | | Queries | 1 mask query | | Decoder blocks | 4 | | Input size | 512 × 512 | | Parameters | ~304M (only ~1M trainable with LoRA) | ## Usage **Repository:** [GitHub](https://github.com/KahimWong/GenText-Forensics-3rd-Place) | **Checkpoint:** [Jason37437/SEED](https://huggingface.co/Jason37437/SEED) / [Google Drive](https://drive.google.com/file/d/1XRbcE2eEdSBdQbyiImg5w9Dn5oMRMKhv/view?usp=drive_link) ```python 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) | Dataset | F1 | |---------|-----| | T-SROIE | 0.782 | | OSTF | 0.718 | | TPIC-13 | 0.798 | | RTM | 0.178 | | Avg | 0.619 | ### Detection (image-level F1) | Dataset | F1 | |---------|-----| | T-SROIE | 0.738 | | OSTF | 0.832 | | TPIC-13 | 0.930 | | RTM | 0.207 | | Avg | 0.677 | ## Citation ```bibtex @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.