随着AIGC技术的快速发展，图像编辑工具日益强大，图像篡改变得更加容易，也更难被察觉。 虽然现有的图像篡改检测和定位方法（IFDL）通常很有效，但它们往往面临两大挑战:一是“黑匣子”性质，检测原理不明;二是泛化能力有限，难以应对多种篡改方法(如Photoshop、DeepFake、AIGC编辑)。 为解决这些问题，北京大学的研究团队提出了可解释的IFDL任务，并设计了FakeShield，这是一个多模态框架，能够评估图像的真实性，生成篡改区域掩码，并基于像素级和图像级的篡改线索提供判断依据。传统
["科学期刊Science宣布采用商业软件Proofig，通过AI检测图像篡改，预防不当操控图像的研究欺诈。","尽管软件能够捕捉到一些最严重的图像篡改案例，但了解软件操作方式的欺诈者仍有规避的可能。","图像篡改在科学研究中是一种常见欺诈手段，特别是在实验数据处理中。"]
AI图像检测工具，识别篡改照片
Alibaba
-
Input tokens/M
Output tokens/M
Context Length
$1
$10
256
$2
$20
$3.9
$15.2
64
Bytedance
$0.8
$0.15
$1.5
128
Baidu
32
$8
$1.6
$4
Tencent
24
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
