thu-huangzc/ffaa-mistral-7b

FFAA Model Card

Model details

Model type: Face Forgery Analysis Assistant (FFAA) consists of a fine-tuned MLLM and Multi-answer Intelligent Decision System (MIDS). It is a Multi-modal Large Language Model dedicated to the face forgery analysis. Base MLLM: liuhaotian/llava-v1.6-mistral-7b

Paper or resources for more information: https://ffaa-vl.github.io/

Where to send questions or comments about the model: https://github.com/thu-huangzc/FFAA/issues

Intended use

Primary intended uses: The primary use of FFAA is research on the applications of MLLMs in face forgery analysis, which is essential for understanding the model’s decision-making process and advancing real-world face forgery analysis.

Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.

Training dataset

• 20K face forgery analysis VQA (FFA-VQA) dataset, captioned by GPT-4o.

• 90K historical answer data generated by the MLLM fine-tuned on FFA-VQA.

Evaluation dataset

Open-World Face Forgery Analysis Benchmark (OW-FFA-Bench), including 6 face forgery generalization test sets. The download link is Google driver