Abstract
Portrait composition plays a central role in portrait aesthetics and visual communication, yet existing datasets and benchmarks mainly focus on coarse aesthetic scoring, generic image aesthetics, or unconstrained portrait generation. This limits systematic research on structured portrait composition analysis and controllable portrait generation under explicit composition requirements. In this paper, we introduce PortraitCraft, a unified benchmark for portrait composition understanding and generation. PortraitCraft is built on a dataset of approximately 50,000 curated real portrait images with structured multi-level supervision, including global composition scores, annotations over 13 composition attributes, attribute-level explanation texts, visual question answering pairs, and composition-oriented textual descriptions for generation. Based on this dataset, we establish two complementary benchmark tasks for composition understanding and composition-aware generation within a unified framework. The first evaluates portrait composition understanding through score prediction, fine-grained attribute reasoning, and image-grounded visual question answering, while the second evaluates portrait generation from structured composition descriptions under explicit composition constraints. We further define standardized evaluation protocols and provide reference baseline results with representative multimodal models. PortraitCraft provides a comprehensive benchmark for future research on fine-grained portrait understanding, interpretable aesthetic assessment, and controllable portrait generation.
Abstract (translated)
肖像构图在肖像美学与视觉传播中起着核心作用，然而现有数据集与基准主要集中于粗粒度的美学评分、通用图像美学或无约束肖像生成，这限制了在显式构图要求下对结构化肖像构图分析与可控肖像生成的系统研究。本文提出 PortraitCraft，一个统一的肖像构图理解与生成基准。该基准基于约5万张精心筛选的真实肖像图像数据集构建，包含结构化多层次监督信息，如全局构图评分、13项构图属性标注、属性级解释文本、视觉问答对以及面向构图的生成文本描述。基于此数据集，我们在统一框架下建立了两个互补的基准任务：构图理解与构图感知生成。前者通过评分预测、细粒度属性推理与图像导向的视觉问答评估肖像构图理解能力；后者则在显式构图约束下，从结构化构图描述生成肖像图像。我们还定义了标准化评估协议，并为代表性多模态模型提供了参考基线结果。PortraitCraft 为未来精细肖像理解、可解释美学评估与可控肖像生成研究提供了综合性基准。
URL
https://arxiv.org/abs/2604.03611
