Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?

Understand

Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two core capabilities: \textbf{\textit{composition}} and \textbf{\textit{reasoning}}.

• Despite recent advances of T2I models in both composition and reasoning, existing benchmarks remain limited in evaluation.
• They not only fail to provide comprehensive coverage across and within both capabilities, but also largely restrict evaluation to low scene density and simple one-to-one reasoning.
• To address these limitations, we propose \textbf{\textsc{T2I-CoReBench}}, a comprehensive and complex benchmark that evaluates both composition and reasoning capabilities of T2I models.