AesCode: Aesthetic Code Generation with Decoupled Cross-Modal Rewards· AesCode: 结合跨模态奖励的美学代码生成
Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the outputs are structured, editable, and verifiable. Yet code models cannot see how their choices of layout and color come together on the canvas, often limiting spatial planning and aesthetic quality. Image generators excel at visual design but can misrender requested content, making their outputs unreliable targets for direct reproduction. We therefore introduce AesCode, which generates code grounded in the content prompt while using an image generated from the same prompt as an aesthetic guidance. To do so, AesCode represents the target as a design graph that describes the whole canvas and makes each property attributable. From this graph, we derive complementary cross-moda
AesCode 利用跨模态奖励生成具有美学效果的代码。
- 核心方法
- AesCode 通过构建设计图来描述整个画布，并为每个属性分配值，结合内容提示生成代码，同时使用同一提示生成的图像作为美学指导。
- 适合谁读
- 研究者、工程师
- 要解决的问题
- 现有代码生成模型难以结合视觉设计中的布局和色彩美学，而图像生成器虽然在视觉设计上表现良好，但直接生成的内容不可靠。
- 关键实验
- 展示了 AesCode 在生成幻灯片、海报和仪表板代码时的优越性能和美学效果。
- 主要贡献
- 提出了一种新的跨模态融合方法，提高了代码生成的视觉美学和可靠性。
- 意义与局限
- 该方法可以增强代码生成的实用性和美学质量，但可能在复杂设计和个性化需求上存在局限。