從提示詞到構圖：用於海報生成的 Spatial Canvas Interface
From Prompting to Composing: A Spatial Canvas Interface for Poster Generation
研究提出 Spatial Canvas Interface，讓用戶在空間畫布上編排海報生成意圖，並據此開發模型 Compo。介面提供語義、身份、文字及像素四種綁定方式，並以 Text Specifications 描述個別元素與整體外觀。評測顯示，Compo 的構圖可控性強於通用圖像生成模型及專用海報生成系統，同時維持高視覺質素。
Published on Oct 8
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Abstract
Text prompting is an indirect interface for poster generation, requiring users to encode inherently two-dimensional composition intent into a one-dimensional sequence of words. We introduce a Spatial Canvas Interface that enables users to directly compose generation intent in space through four complementary binding types: semantic, identity, text, and pixel, together with Text Specifications for individual elements and global appearance. Based on this interface, we develop Compo, a poster generation model adapted from a pretrained image editing model to understand Spatial Canvas inputs and Text Specifications. Compo supports both direct inference, where users explicitly construct the canvas, and agentic mode, where a high-level request is automatically translated into a planned Spatial Canvas. To train Compo, we develop a scalable pipeline that automatically constructs supervision data for different binding types and their combinations, enabling efficient adaptation without training a specialized poster generator from scratch. We further introduce a benchmark that evaluates adherence to individual binding types and their joint composition. Experiments show that Compo achieves stronger compositional controllability than both general-purpose image generation models and dedicated poster generation systems while maintaining high visual quality. By decoupling intent specification from visual generation, our work shifts poster generation from prompting toward composing.
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來源：HuggingFace Daily Papers（社區熱門論文） · huggingface.co