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FakeBench: Uncover the Achilles' Heels of Fake Images with Large Multimodal Models
April 23, 2024, 4:46 a.m. | Yixuan Li, Xuelin Liu, Xiaoyang Wang, Shiqi Wang, Weisi Lin
cs.CV updates on arXiv.org arxiv.org
Abstract: Recently, fake images generated by artificial intelligence (AI) models have become indistinguishable from the real, exerting new challenges for fake image detection models. To this extent, simple binary judgments of real or fake seem less convincing and credible due to the absence of human-understandable explanations. Fortunately, Large Multimodal Models (LMMs) bring possibilities to materialize the judgment process while their performance remains undetermined. Therefore, we propose FakeBench, the first-of-a-kind benchmark towards transparent defake, consisting of fake …
abstract artificial artificial intelligence arxiv become binary challenges credible cs.cv cs.mm detection fake generated image image detection images intelligence large multimodal models multimodal multimodal models simple type
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