How Far Can Coding Agents Go in Visual Generation?
Modern image generation largely relies on specialized generative models that leave the process of image construction implicit in learned parameters. We explore an alternative: general-purpose coding agents that construct images through executable programs. Our study of zero-shot drawing on AgentDrawBench, a 200-prompt benchmark, reveals a distinctive capability profile. Agents excel at preserving structure and satisfying precise visual constraints, achieving competitive results in domains where compositional accuracy matters more than photorealistic appearance, while remaining limited in perceptual richness. Their visual expressiveness varies with the drawing interface, and a qualitative ...
| Authors | Hengguang Zhou, Yuanhao Ban, Jiaqi Feng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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