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Robbyant/lingbot-map

A geometric context transformer foundation model for streaming 3D reconstruction

Edition 10 OCT 2026 · NO. 10
Stars
★ 17.7k
Language
Python
Chart appearances
3
On-chart tracking
1 days tracked

What it does

LingBot-Map is a feed-forward 3D foundation model focused on streaming 3D reconstruction. Its Geometric Context Transformer unifies coordinate grounding, dense geometric cues, and long-range drift correction within a single streaming framework for efficient, stable online reconstruction.

What's inside

The repo contains inference code, an interactive demo.py, an offline rendering pipeline in demo_render/batch_demo.py, plus installation instructions, model download links, and evaluation benchmark scripts.

Tech stack

Implemented in Python with PyTorch and attention backends (FlashInfer / SDPA), using paged KV cache attention to support long-sequence inference.

Use cases

  • 3D reconstruction and SLAM researchers for streaming reconstruction and long-sequence drift correction experiments
  • Robotics/AR-VR developers needing real-time online 3D perception and mapping
  • Computer vision engineers evaluating feed-forward 3D foundation models on benchmarks

Why it's trending

As an ECCV 2026 Best Paper Award candidate, it quickly gained 17,703 stars thanks to ~20 FPS streaming inference and stable reconstruction over 10,000+ frames, adding 110 stars today and ranking 10th on GitHub Trending daily.

Current chart placements

PeriodLanguage filterRankStars gained
DailyAll languages#10+110
DailyPython#3+110
WeeklyPython#7+446

Editorial summaries are based on the public repository and the dated GitHub Trending snapshot. Verify implementation details in the upstream repository.

Open repository on GitHub ↗