Paper Banana
PaperBanana (Paper Banana) is a web-based academic illustration generator that converts research paper text, reference images, or rough sketches into publication-ready figures. It focuses specifically on scientific and technical visuals such as methodology pipeline diagrams, model architecture block diagrams, statistical plot panels, graphical abstracts, poster panels, and educational infographics, rather than general-purpose AI art. The product exposes several distinct entry points in its app: an Image-to-Image tool for generating figures from uploaded sketches, screenshots, or reference images; an AI Image Editor for revising and cleaning existing visuals with text instructions; and an AI Image Upscaler for improving resolution and clarity of low-quality drafts. Users can also start from a library of curated prompt templates covering common research figure patterns such as RAG pipelines, transformer architectures, benchmark plots, and sketch cleanup. A typical workflow begins with describing the desired figure or pasting paper context, optionally supplying reference material, then choosing a visual style. According to the homepage, sign-in is required before generation, free draft previews are provided to test an idea, and paid models are recommended when cleaner labels and more publication-ready output are needed. The site references Nano Banana and Nano Banana Pro as underlying image models. The positioning is explicitly aimed at researchers rather than generic AI image generation, emphasizing consistent labels, readable arrows, structured panels, and diagram conventions suitable for papers, talks, and posters.
- Category
- Image Gen
- Pricing
- Free
Problem solved
Producing clear, consistent figures for papers, posters, and presentations is slow and often requires manual drawing or diagramming skills. PaperBanana addresses this by turning paper text, references, or rough sketches into publication-ready methodology diagrams, architecture diagrams, statistical plots, and poster panels, and by offering editing and upscaling tools to clean up existing drafts.
Use cases
- Generate a methodology pipeline diagram from a paper's method section
- Convert a rough hand-drawn sketch into a polished academic diagram
- Create model architecture block diagrams showing encoders, retrievers, and fusion steps
- Produce multi-panel statistical plots such as ablation, accuracy, and latency charts
- Build multi-panel poster layouts covering problem, method, results, and impact
- Clean up and relabel existing research figures with text instructions
- Upscale low-resolution screenshots or drafts of figures for final export
- Create graphical abstracts and educational infographics for papers and talks
Audience
- Researchers
- ML Engineers
- Data Scientists
- Content Creators
Pros
- Purpose-built for academic and research figures rather than generic AI art
- Multiple entry points covering generation from references, editing, and upscaling
- Prompt library with ready-made research figure patterns
- Free draft previews allow testing ideas before paying
- Supports common paper visuals such as pipelines, architectures, and plot panels
Cons
- Sign-in required before generation
- Full publication-quality output is tied to paid models
- No GitHub repository or open-source code published
- Limited transparency about underlying models and data handling
- Not intended for general-purpose creative or photographic image generation
Official website: https://paperbana.com/
Canonical LambdaBase page: https://www.lambdabase.com/tools/paper-banana