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How to rebuild the figure dataset with the curation pipeline with Topconf Paper Figure Gallery

Run the documented scripts to regenerate the gallery data from proceedings and PDFs.

  • Research
  • Advanced
  • 2 hours
  • From the README
  • Any agent

Who it is forA maintainer or research engineer who wants to extend the dataset to new venues or check how the gallery was built.

The problemAdding a new conference or auditing the selection rules requires running the full pipeline from proceedings index to manual review.

The outcomeA regenerated figures.json and figures.js built from a candidate pool, following the documented pipeline order.

What you need first

  • A modern web browser
  • Git and Python 3 if you want to run the gallery locally
  • An API key from a model provider you choose, only for FigureForge generation
  • The title and abstract of your paper, or one sentence describing its input, method and output

Steps

  1. Run pip install -r requirements.txt
  2. Run python scripts/build_pool.py to build the ICLR, ICML and NeurIPS candidate pool
  3. Run python scripts/extract_all.py to download PDFs and crop Figure 1, then python scripts/score_select.py 980 to score and select
  4. Run python scripts/assemble_gallery.py 1000 to generate figures.json and figures.js
  5. Run python scripts/enum_sheets.py iclr and review the contact sheets page by page, as docs/METHODOLOGY.md describes

Prompt for your agent

In a clone of qwdwqfwq/topconf-paper-figure-gallery, install requirements and run the build_pool, extract_all and score_select scripts in that order for a dry run on <venue>. Expected output: a selection count printed by score_select. Verify the count is non-zero and that no figure is copied from the gallery without its source link.

Caveat. The pipeline downloads publisher PDFs, and the README says the images belong to their authors and publishers, so check the image policy before publishing any output.

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