# hustvl/MapTR

[ICLR'23 Spotlight & ECCV'24 & IJCV'24] MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Repository: https://github.com/hustvl/MapTR
Canonical: https://ross.abutalabs.com/products/maptr
Language: Python
License: MIT
License Family: permissive
Topics: bev, end-to-end, real-time, transformer, online-hdmap-construction, shape-representation, vectorized-hdmap, autonomous-driving, iclr2023
Last push: 2025-03-03T03:06:32+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 9, release rhythm 8, longevity 100
- inputs: {"age_days": 1498, "days_push": 548, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1542, forks 249 (observed 2026-08-28T04:05:01.057626+00:00)

## What it is
MapTR is an end-to-end transformer-based framework for online vectorized HD map construction from camera imagery in autonomous driving. It performs structured modeling and learning of map elements in bird's-eye view in real time, with an extended MapTRv2 variant.

## Use cases
- build vectorized HD maps online from camera sensors
- research bird's-eye-view map perception for autonomous driving
- generate map annotations automatically from driving data
- benchmark real-time HD map construction on nuScenes
- provide map priors for downstream motion planning models

## When to choose
- you need state-of-the-art online vectorized HD map construction from multi-view cameras
- you are doing academic research on BEV perception or end-to-end driving
- you want a real-time map head to plug into an autonomous driving stack

## When to avoid
- you need production-grade mapping with lidar fusion and map maintenance workflows
- you lack GPU resources for training transformer-based perception models
- you need a turnkey commercial HD mapping product rather than research code

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, computer-vision, image-processing
- domain: autonomous-vehicles, computer-vision, deep-learning, machine-learning
- platform: python
- tags: hd-map-construction, bev-perception, transformer, end-to-end, vectorized-maps, autonomous-driving, research-code, iclr2023, linux, gpu

## Member repositories
- hustvl/MapTR (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:01.057626+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:30:44.778701+00:00, confidence not recorded.
  - readme: https://github.com/hustvl/MapTR (fetched 2026-08-28T04:05:01.057626+00:00, sha 63c7194cacb0)
- Data as of 2026-08-30T08:39:29.467469+00:00.