CVPR 2026 Explorer

A 2D semantic map of all 4068 CVPR 2026 papers, built from SPECTER2 embeddings of their abstracts. Nearby points are semantically similar papers, so a cluster is a topic.

Live site: https://flecomet.github.io/cvpr-explorer/

This is a fork of dataplayer12/cvpr-explorer (cvprexplorer.com), rewritten for CVPR 2026: OpenAI embeddings replaced with the open SPECTER2 scientific-document model, automatic cluster labels, and a static front-end that needs no server. Original idea and design credit to @dataplayer12. Same license as upstream — see LICENSE.

Why

Conference sites list 4000+ papers as one flat list. Finding the ones you care about means scrolling past thousands you don't. Here you zoom into the region of the map you're interested in — diffusion, 3D reconstruction, medical imaging — and read only those.

How it works

The pipeline is offline; the site is static.

Step	Script	Output
Scrape titles, authors, abstracts, PDF links	scrape.py	data/cvpr_2026_papers.json
Embed abstracts with SPECTER2	embed.py	data/cvpr_2026_specter2.npy
UMAP to 2D + HDBSCAN clusters + c-TF-IDF labels	layout.py	data/cvpr_2026_layout.json
Merge into the site payload	build_site.py	site/data.json

site/index.html renders that payload client-side with plotly.js. No backend, no API keys at serve time.

Run the pipeline

pip install -r requirements-pipeline.txt
python scrape.py     # writes data/cvpr_2026_papers.json
python embed.py      # writes data/cvpr_2026_specter2.npy (GPU recommended)
python layout.py     # writes data/cvpr_2026_layout.json

Serve locally

Static site (what the live URL serves):

python build_site.py
python -m http.server -d site 8000   # http://localhost:8000

Or the original Dash app:

pip install -r requirements.txt
python app.py                        # http://localhost:8050

Or with Docker:

docker compose build
docker compose up

Deployment

Pushing to main runs .github/workflows/pages.yml, which rebuilds site/data.json and publishes site/ to GitHub Pages.

Roadmap

• SPECTER2 embeddings (open model, no API key)
• 2D projection with clusters and automatic topic labels
• Static site — no server, no cold start
• Keyword search across titles and abstracts
• Mark papers with released code
• Add more conferences and years back