Summary of Forgerygpt: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization, by Jiawei Liu et al.
ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization
by Jiawei Liu, Fanrui Zhang, Jiaying Zhu, Esther Sun, Qiang Zhang, Zheng-Jun Zha
First submitted to arxiv on: 14 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes ForgeryGPT, a novel framework for Image Forgery Detection and Localization (IFDL) that leverages multimodal large language models like GPT4o to capture high-order forensics knowledge correlations. The framework integrates the Mask-Aware Forgery Extractor, which enables precise forgery mask information extraction from input images. This extractor consists of a Forgery Localization Expert and a Mask Encoder, augmented with an Object-agnostic Forgery Prompt and a Vocabulary-enhanced Vision Encoder. To enhance performance, the paper implements a three-stage training strategy supported by designed datasets for Mask-Text Alignment and IFDL Task-Specific Instruction Tuning. The proposed method demonstrates effectiveness in extensive experiments. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to detect fake images on the internet. Right now, computers are not very good at this task because they only look at simple features like colors and shapes. But humans can recognize fake images by looking at many different clues, like language patterns and object locations. The researchers propose a new computer model called ForgeryGPT that can learn to detect fake images in the same way humans do. They also develop special tools to help the computer understand why an image is fake or real. This is important because fake images are becoming more common on the internet, and we need better ways to spot them. |
Keywords
» Artificial intelligence » Alignment » Encoder » Instruction tuning » Mask » Prompt
