Any2Poster vs PosterGen
Any2Poster
any2poster.github.ioPosterGen
github.comSide by side
| Figure | Any2Poster | PosterGen |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 0 |
| Spec score · AI Poster Generators | 7.8 (#11) | 7.5 (#16) |
| Intended audience | The project describes its output as academic posters and provides an evaluation benchmark for poster generation across input formats and content domains. | The README describes conference poster design and identifies the output as professional academic posters. |
| Outputs | The project lists PDF, PNG, and HTML artifact outputs. | The system produces PNG poster images and editable PowerPoint files. |
| Purpose | Any2Poster turns documents, slideshows, notebooks, and videos into publication-quality academic posters. | PosterGen generates academic posters from research papers using a multi-agent large language model framework guided by design principles. |
| Requirements | The project lists Python 3.10 or later and requires installing the Playwright Chromium browser for rendering. | The README specifies Python 3.11 and requires LibreOffice; its web interface also requires Node.js and configured API keys. |
| Workflow | Its six-stage pipeline parses, chunks, analyzes, plans, generates, and compiles posters, with checkpoints that allow resuming a run. | Its workflow uses parser, curator, layout and styling agents to extract paper content, plan a narrative storyboard, arrange a three-column layout and apply colors and typography. |
In their own words
Any2Poster
Any2Poster converts source material into academic posters and produces PDF, PNG, and HTML artifacts. It accepts documents and presentations, LaTeX, Markdown, plain text, Jupyter notebooks, HTML, URLs, and YouTube URLs. Its six-stage process parses, chunks, analyzes, plans, generates, and compiles posters; saved checkpoints let a run resume from cached stages. Poster text is rendered with HTML and CSS through Playwright, which the project says avoids typography hallucination. Suitable figures can be extracted from the source, while AI image generation can supply panels without a suitable figure. An optional panel-level review checks overflow, blank space, font size, figure balance, and reading order. Users can select named themes, use automatic theme selection, or set custom colors and poster dimensions. The project is open source under an MIT license, with source and Docker installation instructions for Windows, macOS, and Linux. Setup requires Python 3.10 or newer, the Playwright Chromium browser, and an OPENROUTER_API_KEY. A web interface is marked as coming soon.
PosterGen
PosterGen generates academic posters from research paper PDFs, using a multi-agent language-model workflow to extract content, plan a narrative, arrange the layout, and apply styling. Its Parser Agent structures paper content, while the Curator Agent plans organization and visual placement. Layout and Balancer agents calculate spacing and column use, with the Balancer addressing overflow. Styling includes colors drawn from an affiliation logo, professional font choices, and keyword highlighting. Users can adjust layout, typography, color generation, visual asset sizing, and content optimization through configuration. A local web interface accepts a paper PDF and logos, lets users configure models and poster dimensions, and generates a PNG plus an editable PowerPoint file. Documented width-to-height ratios run from 1.4 to 2, and custom dimensions are supported. The project lists Windows, Linux, and macOS, but setup requires Python 3.11 and LibreOffice; the web interface also needs Node.js and configured API keys. Setup documents OpenAI, Anthropic, and Zhipu keys, with configurable service base URLs including Google. PosterGen is free and MIT-licensed; the license provides the software without warranty.