AI-Generated Image Detection using a Cross-Attention Enhanced Dual-Stream Network

Understand

With the rapid evolution of AI Generated Content (AIGC), forged images produced through this technology are inherently more deceptive and require less human intervention compared to traditional Computer-generated Graphics (CG).

• However, owing to the disparities between CG and AIGC, conventional CG detection methods tend to be inadequate in identifying AIGC-produced images.
• To address this issue, our research concentrates on the text-to-image generation process in AIGC.
• Initially, we first assemble two text-to-image databases utilizing two distinct AI systems, DALLE2 and DreamStudio.