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1 | Method | Title | Venue | First appearance date | Accepted Year | Method | Task | Paper URL | Preprint URL | Implementation URL | |||||||||||||||||||
2 | AdaGridDoc | Adaptive grid-based document layout | TOG | 2003/07/01 | 2003 | not NN | レイアウト生成 | https://doi.org/10.1145/882262.882353 | |||||||||||||||||||||
3 | Label Layout Styles | Specifying label layout style by example | UIST | 2007/10/07 | 2007 | not NN | レイアウト生成 | https://doi.org/10.1145/1294211.1294252 | |||||||||||||||||||||
4 | Survey-1 | Design principles for visual communication | Communications of the ACM | 2011/04/01 | 2011 | Survey | レイアウト生成 | https://doi.org/10.1145/1924421.1924439 | |||||||||||||||||||||
5 | Furniture Layout Guidelines | Interactive furniture layout using interior design guidelines | SIGGRAPH | 2011/07/25 | 2011 | not NN | レイアウト生成 | https://doi.org/10.1145/1964921.1964982 | |||||||||||||||||||||
6 | DesignLayout | Learning Layouts for Single-PageGraphic Designs | TVCG | 2014/03/21 | 2014 | not NN | レイアウト生成 | https://doi.org/10.1109/TVCG.2014.48 | |||||||||||||||||||||
7 | DesignScape | DesignScape: Design with Interactive Layout Suggestions | CHI | 2015/04/18 | 2015 | not NN | レイアウト生成 | https://doi.org/10.1145/2702123.2702149 | |||||||||||||||||||||
8 | FID | GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium | NeurIPS | 2017/06/26 | 2017 | Metrics | 画像生成 | https://dl.acm.org/doi/10.5555/3295222.3295408 | https://arxiv.org/abs/1706.08500 | https://github.com/mseitzer/pytorch-fid | |||||||||||||||||||
9 | Rico | Rico: A Mobile App Dataset for Building Data-Driven Design Applications | CHI | yyyy/mm/dd | 2017 | Dataset | レイアウト生成 | https://dl.acm.org/doi/10.1145/3126594.3126651 | http://www.interactionmining.org/rico.html | ||||||||||||||||||||
10 | LayoutGAN | LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators | ICLR | 2019/01/19 | 2019 | GAN | レイアウト生成 | https://openreview.net/forum?id=HJxB5sRcFQ | https://arxiv.org/abs/1901.06767 | ||||||||||||||||||||
11 | ContentGAN | Content-aware generative modeling of graphic design layouts | SIGGRAPH | 2019/07/12 | 2019 | GAN | レイアウト生成 | https://doi.org/10.1145/3306346.3322971 | https://xtqiao.com/projects/content_aware_layout/ | ||||||||||||||||||||
12 | LayoutVAE | LayoutVAE: Stochastic Scene Layout Generation From a Label Set | ICCV | 2019/07/24 | 2019 | VAE | レイアウト生成 | https://doi.org/10.1109/ICCV.2019.00999 | https://arxiv.org/abs/1907.10719 | ||||||||||||||||||||
13 | PubLayNet | PubLayNet: largest dataset ever for document layout analysis | ICDAR | 2019/08/16 | 2019 | Dataset | レイアウト生成 | https://doi.ieeecomputersociety.org/10.1109/ICDAR.2019.00166 | https://arxiv.org/abs/1908.07836 | https://github.com/ibm-aur-nlp/PubLayNet | |||||||||||||||||||
14 | READ | READ: Recursive Autoencoders for Document Layout Generation | CVPR-W | 2019/09/01 | 2020 | VAE | レイアウト生成 | https://doi.org/10.1109/CVPRW50498.2020.00280 | https://arxiv.org/abs/1909.00302 | ||||||||||||||||||||
15 | NDN | Neural Design Network: Graphic Layout Generation with Constraints | ECCV | 2019/12/19 | 2020 | VAE | レイアウト生成 | https://doi.org/10.1007/978-3-030-58580-8_29 | https://arxiv.org/abs/1912.09421 | ||||||||||||||||||||
16 | Fidelity&Diversity | Reliable Fidelity and Diversity Metrics for Generative Models | ICML | 2020/02/23 | 2020 | Metrics | 画像生成 | https://dl.acm.org/doi/abs/10.5555/3524938.3525603 | https://arxiv.org/abs/2002.09797 | https://github.com/clovaai/generative-evaluation-prdc | |||||||||||||||||||
17 | SmartText | Smarttext: Learning To Generate Harmonious Textual Layout Over Natural Image | TMM | 2020/06/09 | 2022 | System Framework | ポスター生成 | https://dl.acm.org/doi/10.1109/TMM.2021.3097900 | |||||||||||||||||||||
18 | LayoutTransformer | LayoutTransformer: Layout Generation and Completion with Self-attention | ICCV | 2020/06/25 | 2021 | Auto-regressive | レイアウト生成 | https://doi.org/10.1109/ICCV48922.2021.00104 | https://arxiv.org/abs/2006.14615 | https://github.com/kampta/DeepLayout | |||||||||||||||||||
19 | AC-LayoutGAN | Attribute-conditioned Layout GAN for Automatic Graphic Design | TVCG | 2020/09/11 | 2021 | GAN | レイアウト生成 | https://doi.org/10.1109/TVCG.2020.2999335 | https://arxiv.org/abs/2009.05284 | ||||||||||||||||||||
20 | LayoutGCN | Learning Structural Similarity of User Interface Layouts Using Graph Networks | ECCV | 2020/11/17 | 2020 | GCN | レイアウト生成 | https://doi.org/10.1007/978-3-030-58542-6_44 | https://github.com/dips4717/gcn-cnn | ||||||||||||||||||||
21 | VINS | VINS: Visual Search for Mobile User Interface Design | CHI | 2021/02/10 | 2021 | Dataset | レイアウト生成 | https://dl.acm.org/doi/10.1145/3411764.3445762 | https://arxiv.org/abs/2102.05216 | https://github.com/sbunian/VINS | |||||||||||||||||||
22 | VTN | Variational Transformer Networks for Layout Generation | CVPR | 2021/04/06 | 2021 | Auto-regressive | レイアウト生成 | https://doi.org/10.1109/CVPR46437.2021.01343 | https://arxiv.org/abs/2104.02416 | ||||||||||||||||||||
23 | RUITE | RUITE: Refining UI Layout Aesthetics Using Transformer Encoder | IUI | 2021/04/14 | 2021 | Auto-regressive | レイアウト生成 | https://dl.acm.org/doi/10.1145/3397482.3450716 | https://github.com/vinothpandian/RUITE | ||||||||||||||||||||
24 | Vinci | Vinci: An Intelligent Graphic Design System for Generating Advertising Posters | SIGGRAPH | 2021/05/07 | 2021 | System Framework | ポスター生成 | https://doi.org/10.1145/3411764.3445117 | https://vinci.idvxlab.com:7000/ | ||||||||||||||||||||
25 | CLG-LO | Constrained Graphic Layout Generation via Latent Optimization | ACMMM | 2021/08/02 | 2021 | Auto-regressive | レイアウト生成 | https://doi.org/10.1145/3474085.3475497 | https://arxiv.org/abs/2108.00871 | ||||||||||||||||||||
26 | CanvasVAE | CanvasVAE: Learning to Generate Vector Graphic Documents | ICCV | 2021/08/03 | 2021 | VAE | ポスター生成 | https://doi.org/10.1109/ICCV48922.2021.00543 | https://arxiv.org/abs/2108.01249 | https://github.com/CyberAgentAILab/canvas-vae | |||||||||||||||||||
27 | De-rendering | De-rendering Stylized Texts | ICCV | 2021/10/05 | 2021 | System Framework | ポスター生成 | https://doi.org/10.1109/ICCV48922.2021.00111 | https://arxiv.org/abs/2110.01890 | ||||||||||||||||||||
28 | LayoutMCL | Diverse Multimedia Layout Generation with Multi Choice Learning | ACMMM | 2021/10/17 | 2021 | Auto-regressive | レイアウト生成 | https://doi.org/10.1145/3474085.3475525 | https://arxiv.org/abs/2301.06629 | ||||||||||||||||||||
29 | BLT | BLT: Bidirectional Layout Transformer for Controllable Layout Generation | ECCV | 2021/12/09 | 2022 | Auto-regressive | レイアウト生成 | https://doi.org/10.1007/978-3-031-19790-1_29 | https://arxiv.org/abs/2112.05112 | ||||||||||||||||||||
30 | CGL-GAN | Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs | IJCAI | 2022/04/30 | 2022 | GAN | ポスター生成 | https://doi.org/10.24963/ijcai.2022/692 | https://arxiv.org/abs/2205.00303 | https://github.com/ktrk115/const_layout | |||||||||||||||||||
31 | Coarse-to-Fine | Coarse-to-Fine Generative Modeling for Graphic Layouts | AAAI | 2022/06/28 | 2022 | VAE | レイアウト生成 | https://doi.org/10.1609/aaai.v36i1.19994 | |||||||||||||||||||||
32 | LayoutFormer++ | LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restriction | CVPR | 2022/08/17 | 2023 | Auto-regressive | レイアウト生成 | https://doi.org/10.1109/CVPR52729.2023.01765 | https://arxiv.org/abs/2208.08037 | https://github.com/microsoft/LayoutGeneration/tree/main/LayoutFormer%2B%2B | |||||||||||||||||||
33 | ICVT (Conference) | Geometry Aligned Variational Transformer for Image-conditioned Layout Generation | ACMMM | 2022/09/02 | 2022 | Auto-regressive | ポスター生成 | https://doi.org/10.1145/3503161.3548332 | https://arxiv.org/abs/2209.00852 | ||||||||||||||||||||
34 | CreaGAN | CreaGAN: An Automatic Creative Generation Framework for Display Advertising | ACMMM | 2022/10/10 | 2022 | GAN | ポスター生成 | https://dl.acm.org/doi/10.1145/3503161.3548763 | |||||||||||||||||||||
35 | LayoutDETR | LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer | ECCV | 2022/12/19 | 2024 | Auto-regressive | ポスター生成 | https://arxiv.org/abs/2212.09877 | https://github.com/salesforce/LayoutDETR | ||||||||||||||||||||
36 | LayoutPGGAN | Machine Learning Model to Evaluate the Appropriateness of Layout for Automatic Generation of Graphic Design Works | IMCOM | 2023/01/03 | 2023 | GAN | ポスター生成 | https://ieeexplore.ieee.org/document/10035646 | |||||||||||||||||||||
37 | Text2Poster | Text2Poster: Laying out Stylized Texts on Retrieved Images | ICASSP | 2023/01/06 | 2022 | VAE | ポスター生成 | https://doi.org/10.1109/ICASSP43922.2022.9747465 | https://arxiv.org/abs/2301.02363 | https://github.com/chuhaojin/Text2Poster-ICASSP-22 | |||||||||||||||||||
38 | PLay | PLay: Parametrically Conditioned Layout Generation using Latent Diffusion | ICML | 2023/01/27 | 2023 | Diffusion Model | レイアウト生成 | https://dl.acm.org/doi/10.5555/3618408.3618624 | https://arxiv.org/abs/2301.11529 | ||||||||||||||||||||
39 | DLT | DLT: Conditioned layout generation with Joint Discrete-Continuous Diffusion Layout Transformer | ICCV | 2023/03/07 | 2023 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2303.03755 | |||||||||||||||||||||
40 | LDGM | Unifying Layout Generation with a Decoupled Diffusion Model | CVPR | 2023/03/09 | 2023 | Diffusion Model | レイアウト生成 | https://doi.org/10.1109/CVPR52729.2023.00193 | https://arxiv.org/abs/2303.05049 | ||||||||||||||||||||
41 | LayoutDM-Inoue | LayoutDM: Discrete Diffusion Model for Controllable Layout Generation | CVPR | 2023/03/14 | 2023 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2303.08137 | https://github.com/CyberAgentAILab/layout-dm | ||||||||||||||||||||
42 | LayoutDiffusion-Zhang | LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models | ICCV | 2023/03/21 | 2023 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2303.11589 | https://github.com/microsoft/LayoutGeneration/tree/main/LayoutDiffusion | ||||||||||||||||||||
43 | PosterLayout | PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layout | CVPR | 2023/03/28 | 2023 | GAN | ポスター生成 | https://arxiv.org/abs/2303.15937 | https://github.com/PKU-ICST-MIPL/PosterLayout-CVPR2023 | ||||||||||||||||||||
44 | LayoutDiffusion-Zheng | LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation | CVPR | 2023/03/30 | 2023 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2303.17189 | https://github.com/ZGCTroy/LayoutDiffusion | ||||||||||||||||||||
45 | FlexDM | Towards Flexible Multi-modal Document Models | CVPR | 2023/03/31 | 2023 | BERT | ポスター生成 | https://arxiv.org/abs/2303.18248 | https://github.com/CyberAgentAILab/flex-dm | ||||||||||||||||||||
46 | LayoutVQ-VAE | Layout Generation for Various Scenarios in Mobile Shopping Applications | CHI | 2023/04/19 | 2023 | VAE | レイアウト生成 | https://dl.acm.org/doi/10.1145/3544548.3581446 | |||||||||||||||||||||
47 | LayoutDM-Chai | LayoutDM: Transformer-based Diffusion Model for Layout Generation | CVPR | 2023/05/04 | 2023 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2305.02567 | |||||||||||||||||||||
48 | TextDiffuser | TextDiffuser: Diffusion Models as Text Painters | NeurIPS | 2023/05/18 | 2023 | Diffusion Model | ポスター生成 | https://arxiv.org/abs/2305.10855 | https://github.com/microsoft/unilm/tree/master/textdiffuser | ||||||||||||||||||||
49 | LayoutGPT | LayoutGPT: Compositional Visual Planning and Generation with Large Language Models | NeurIPS | 2023/05/24 | 2023 | LLM/VLM | レイアウト生成 | https://arxiv.org/abs/2305.15393 | https://github.com/weixi-feng/LayoutGPT | ||||||||||||||||||||
50 | PDA-GAN | Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation | CVPR | 2023/05/25 | 2023 | GAN | ポスター生成 | https://arxiv.org/abs/2303.14377 | |||||||||||||||||||||
51 | Layout Action | Layout Generation as Intermediate Action Sequence Prediction | AAAI | 2023/06/26 | 2023 | Auto-regressive | レイアウト生成 | https://doi.org/10.1609/aaai.v37i9.26277 | |||||||||||||||||||||
52 | RADM | Relation-Aware Diffusion Model for Controllable Poster Layout Generation | CIKM | 2023/06/15 | 2023 | Diffusion Model | ポスター生成 | https://arxiv.org/abs/2306.09086 | https://github.com/liuan0803/RADM | ||||||||||||||||||||
53 | AutoPoster | AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation | ACMMM | 2023/08/02 | 2023 | System Framework | ポスター生成 | https://arxiv.org/abs/2308.01095 | |||||||||||||||||||||
54 | TextPainter | TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design | ACMMM | 2023/08/09 | 2023 | System Framework | ポスター生成 | https://arxiv.org/abs/2308.04733 | https://tianchi.aliyun.com/dataset/160034 | ||||||||||||||||||||
55 | Learn and Sample Together | Learn and Sample Together: Collaborative Generation for Graphic Design Layout | IJCAI | 2023/08/19 | 2023 | GCN | レイアウト生成 | https://doi.org/10.24963/ijcai.2023/649 | |||||||||||||||||||||
56 | Parse-Then-Place | A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptions | ICCV | 2023/08/24 | 2023 | Auto-regressive | レイアウト生成 | https://arxiv.org/abs/2308.12700 | https://github.com/microsoft/LayoutGeneration/tree/main/Parse-Then-Place | ||||||||||||||||||||
57 | Survey-2 | A Survey for Graphic Design Intelligence | arXiv | 2023/09/04 | | Survey | レイアウト生成 | https://doi.org/10.48550/arXiv.2309.01371 | |||||||||||||||||||||
58 | LayoutNUWA | LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models | ICLR | 2023/09/18 | 2024 | LLM/VLM | レイアウト生成 | https://arxiv.org/abs/2309.09506 | https://github.com/ProjectNUWA/LayoutNUWA | ||||||||||||||||||||
59 | Survey-3 | Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature Review | CSCW | 2023/10/04 | 2023 | Survey | レイアウト生成 | https://doi.org/10.1145/3610217 | |||||||||||||||||||||
60 | UIGrammar | UI Layout Generation with LLMs Guided by UI Grammar | ICML-W | 2023/10/24 | 2023 | LLM/VLM | レイアウト生成 | https://arxiv.org/abs/2310.15455 | |||||||||||||||||||||
61 | Dolfin | Dolfin: Diffusion Layout Transformers without Autoencoder | ECCV | 2023/10/25 | 2024 | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2310.16305 | |||||||||||||||||||||
62 | Two-stage LayoutDM | Two-stage Content-Aware Layout Generation for Poster Designs | ACMMM | 2023/10/27 | 2023 | Diffusion Model | ポスター生成 | https://dl.acm.org/doi/abs/10.1145/3581783.3612275 | |||||||||||||||||||||
63 | LayoutPrompter | LayoutPrompter: Awaken the Design Ability of Large Language Models | NeurIPS | 2023/11/11 | 2023 | LLM/VLM | レイアウト生成 | https://arxiv.org/abs/2311.06495 | https://github.com/microsoft/LayoutGeneration/tree/main/LayoutPrompter | ||||||||||||||||||||
64 | RALF | Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation | CVPR | 2023/11/22 | 2024 | Auto-regressive | ポスター生成 | https://arxiv.org/abs/2311.13602 | https://github.com/CyberAgentAILab/RALF | ||||||||||||||||||||
65 | COLE | COLE: A Hierarchical Generation Framework for Multi-Layered and Editable Graphic Design | arXiv | 2023/11/28 | | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2311.16974 | https://github.com/graphic-design-generation/graphic-design-generation.github.io | ||||||||||||||||||||
66 | TextDiffuser-2 | TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering | arXiv | 2023/11/28 | 2023 | Diffusion Model | ポスター生成 | https://arxiv.org/abs/2311.16465 | https://github.com/microsoft/unilm/tree/master/textdiffuser-2 | ||||||||||||||||||||
67 | Survey-4 | Intelligent layout generation based on deep generative models: A comprehensive survey | Information Fusion | 2023/12/01 | 2023 | Survey | ポスター生成 | https://doi.org/10.1016/j.inffus.2023.101940 | |||||||||||||||||||||
68 | Planning&Rendering | Planning and Rendering: Towards End-to-End Product Poster Generation | arXiv | 2023/12/14 | 2023 | System Framework | ポスター生成 | https://arxiv.org/abs/2312.08822 | |||||||||||||||||||||
69 | CG4CTR | A New Creative Generation Pipeline for Click-Through Rate with Stable Diffusion Model | WWW | 2024/01/17 | 2024 | System Framework | ポスター生成 | https://dl.acm.org/doi/10.1145/3589335.3648315 | https://arxiv.org/abs/2401.10934 | https://github.com/HaoYang0123/Creative_Generation_Pipeline | |||||||||||||||||||
70 | Spot the Error | Spot the Error: Non-autoregressive Graphic Layout Generation with Wireframe Locator | AAAI | 2024/01/19 | 2024 | BERT | レイアウト生成 | https://arxiv.org/abs/2401.16375 | https://github.com/ffffatgoose/SpotError | ||||||||||||||||||||
71 | LACE | Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints | ICLR | 2024/02/07 | 2024 | Auto-regressive | レイアウト生成 | https://arxiv.org/abs/2402.04754 | https://github.com/puar-playground/LACE | ||||||||||||||||||||
72 | Desigen | Desigen: A Pipeline for Controllable Design Template Generation | CVPR | 2024/03/14 | 2024 | Auto-regressive | ポスター生成 | https://arxiv.org/abs/2403.09093 | https://github.com/whaohan/desigen | ||||||||||||||||||||
73 | LayoutFlow | LayoutFlow: Flow Matching for Layout Generation | ECCV | 2024/03/27 | 2024 | Flow | レイアウト生成 | https://arxiv.org/abs/2403.18187 | |||||||||||||||||||||
74 | PosterLlama | PosterLlama: Bridging Design Ability of Langauge Model to Contents-Aware Layout Generation | ECCV | 2024/04/01 | 2024 | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2404.00995 | |||||||||||||||||||||
75 | Graphist | Graphic Design with Large Multimodal Model | arXiv | 2024/04/22 | | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2404.14368 | https://github.com/graphic-design-ai/graphist | ||||||||||||||||||||
76 | DocLap | Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models | arXiv | 2024/04/23 | | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2404.15271 | |||||||||||||||||||||
77 | DesignProbe | DesignProbe: A Graphic Design Benchmark for Multimodal Large Language Models | arXiv | 2024/04/23 | | Metrics | ポスター生成 | https://arxiv.org/abs/2404.14801 | |||||||||||||||||||||
78 | CoLay | CoLay: Controllable Layout Generation through Multi-conditional Latent Diffusion | arXiv | 2024/05/18 | | Diffusion Model | レイアウト生成 | https://arxiv.org/abs/2405.13045 | |||||||||||||||||||||
79 | RARE+ | Revision Matters: Generative Design Guided by Revision Edits | arXiv | 2024/05/27 | | System Framework | レイアウト生成 | https://arxiv.org/abs/2406.18559 | |||||||||||||||||||||
80 | PostDoc | PostDoc: Generating Poster from a Long Multimodal Document Using Deep Submodular Optimization | arXiv | 2024/05/30 | | System Framework | ポスター生成 | https://arxiv.org/abs/2405.20213 | |||||||||||||||||||||
81 | PosterLLaVa | PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM | arXiv | 2024/06/05 | | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2406.02884 | https://github.com/posterllava/PosterLLaVA | ||||||||||||||||||||
82 | OpenCOLE | OpenCOLE: Towards Reproducible Automatic Graphic Design Generation | arXiv | 2024/06/12 | | LLM/VLM | ポスター生成 | https://arxiv.org/abs/2406.08232 | https://github.com/CyberAgentAILab/OpenCOLE | ||||||||||||||||||||
83 | VLC | Visual Layout Composer: Image-Vector Dual Diffusion Model for Design Layout Generation | CVPR | 2024/06/19 | 2024 | Diffusion Model | ポスター生成 | https://openaccess.thecvf.com/content/CVPR2024/html/Shabani_Visual_Layout_Composer_Image-Vector_Dual_Diffusion_Model_for_Design_Layout_CVPR_2024_paper.html | https://aminshabani.github.io/visual_layout_composer/pdfs/visual_layout_composer.pdf | ||||||||||||||||||||
84 | LTSim | LTSim: Layout Transportation-based Similarity Measure for Evaluating Layout Generation | arXiv | 2024/07/17 | | Metrics | レイアウト生成 | https://arxiv.org/abs/2407.12356 | |||||||||||||||||||||
85 | Multi-constraint LayoutVQ-VAE | Iris: a multi-constraint graphic layout generation system | FITEE | 2024/07/24 | 2024 | VAE | ポスター生成 | https://doi.org/10.1631/FITEE.2300312 | |||||||||||||||||||||
86 | ICVT (Journal) | Self-refined variational transformer for image-conditioned layout generation | IJMLC | 2024/09/16 | 2024 | Auto-regressive | レイアウト生成 | https://doi.org/10.1007/s13042-024-02355-5 | |||||||||||||||||||||
87 | Neural Contrst | Neural Contrast: Leveraging Generative Editing for Graphic Design Recommendations | PRICAI | 2024/09/26 | 2024 | System Framework | ポスター生成 | https://arxiv.org/abs/2410.07211 | |||||||||||||||||||||
88 | graphic-design-evaluation | Can GPTs Evaluate Graphic Design Based on Design Principles? | SIGGRAPH Asia | 2024/10/11 | 2024 | Dataset | ポスター生成 | https://arxiv.org/abs/2410.08885 | https://github.com/CyberAgentAILab/Graphic-design-evaluation | ||||||||||||||||||||
89 | LGGPT | Smaller But Better: Unifying Layout Generation with Smaller Large Language Models | IJCV | 2025/02/12 | 2025 | LLM/VLM | レイアウト生成 | https://doi.org/10.1007/s11263-025-02353-2 | https://github.com/NiceRingNode/LGGPT |