A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptions
Jiawei Lin, Jiaqi Guo, Shizhao Sun, Weijiang Xu, Ting Liu, Jian-Guang Lou, Dongmei Zhang
摘要
Creating layouts is a fundamental step in graphic design. In this work, we propose to use text as the guidance to create graphic layouts, i.e., Text-to-Layout, aiming to lower the design barriers. Text-to-Layout is a challenging task, because it needs to consider the implicit, combined, and incomplete layout constraints from text, each of which has not been studied in previous work. To address this, we present a two-stage approach, named parse-then-place. The approach introduces an intermediate representation (IR) between text and layout to represent diverse layout constraints. With IR, Text-to-Layout is decomposed into a parse stage and a place stage. The parse stage takes a textual description as input and generates an IR, in which the implicit constraints from the text are transformed into explicit ones. The place stage generates layouts based on the IR. To model combined and incomplete constraints, we use a Transformer-based layout generation model and carefully design a way to represent constraints and layouts as sequences. Besides, we adopt the pretrain-then-finetune strategy to boost the performance of the layout generation model with large-scale unlabeled layouts. To evaluate our approach, we construct two Text-to-Layout datasets and conduct experiments on them. Quantitative results, qualitative analysis, and user studies demonstrate our approach’s effectiveness.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper5
- LayoutPrompter: Awaken the Design Ability of Large Language ModelsJiawei Lin, Jiaqi Guo, Shizhao Sun, Zijiang Yang 等NeurIPS 2023 · 被引用 71 次
- Text-to-Code Generation for Modular Building Layouts in Building Information ModelingYinyi Wei, Xiao LiNeurIPS 2025 · 被引用 2 次
- GLDesigner: Leveraging Multi-Modal LLMs as Designer for Enhanced Aesthetic Text Glyph LayoutsJunwen He, Yifan Wang, Lijun Wang, Huchuan Lu 等ACM MM 2025 · 被引用 1 次
- Multimodal Markup Document Models for Graphic Design CompletionKotaro Kikuchi, Ukyo Honda, Naoto Inoue, Mayu Otani 等ACM MM 2025 · 被引用 1 次
- From Elements to Design: A Layered Approach for Automatic Graphic Design CompositionJiawei Lin, Shizhao Sun, Danqing Huang, Ting Liu 等CVPR 2025
它引用的顶会 Paper12
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li 等NeurIPS 2022 · 被引用 8,965 次
- Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray 等ICML 2021 · 被引用 6,356 次
- Pix2Struct: Screenshot Parsing as Pretraining for Visual Language UnderstandingKenton Lee, Mandar Joshi, Iulia Raluca Turc, Hexiang Hu 等ICML 2023 · 被引用 426 次
- UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsTianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong 等EMNLP 2022 · 被引用 222 次
- LayoutVAE: Stochastic Scene Layout Generation From a Label SetAkash Abdu Jyothi, Thibaut Durand, Jiawei He, Leonid Sigal 等ICCV 2019 · 被引用 194 次
相关 Paper
- Constrained Graphic Layout Generation via Latent OptimizationKotaro Kikuchi, Edgar Simo-Serra, Mayu Otani, Kota YamaguchiACM MM 2021 · 被引用 80 次
- Generative Layout Modeling using Constraint GraphsWamiq Para, Paul Guerrero, Tom Kelly, Leonidas J. Guibas 等ICCV 2021 · 被引用 93 次
- LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space RestrictionZhaoyun Jiang, Jiaqi Guo, Shizhao Sun, Huayu Deng 等CVPR 2023
- LayoutTransformer: Scene Layout Generation With Conceptual and Spatial DiversityCheng-Fu Yang, Wan-Cyuan Fan, Fu-En Yang, Yu-Chiang Frank WangCVPR 2021
- PlanGen: Towards Unified Layout Planning and Image Generation in Auto-Regressive Vision Language ModelsRunze He, Bo Cheng, Yuhang Ma, Qingxiang Jia 等ICCV 2025 · 被引用 1 次
