# zhulf0804/3D-PointCloud

Papers and Datasets  about Point Cloud.

Repository: https://github.com/zhulf0804/3D-PointCloud
Canonical: https://ross.abutalabs.com/products/3d-pointcloud
Language: Python
License Family: other
Topics: point-cloud, registration, segmentation, classification, completion, detection, autonomous-driving, generation, papers, datasets, monocular
Last push: 2024-08-30T09:40:10+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2737, "days_push": 733, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2937, forks 329 (observed 2026-08-28T04:07:30.882411+00:00)

## What it is
A curated list of research papers and datasets about 3D point clouds, covering tasks like registration, segmentation, classification, completion, and detection. It serves as a reference resource for researchers in 3D vision and autonomous driving.

## Use cases
- find papers on 3d point cloud registration
- find datasets for point cloud segmentation
- survey of 3d object detection for autonomous driving
- learn about point cloud deep learning methods
- find lidar datasets for self-driving research
- research reading list for 3d vision

## When to choose
- you need a curated reading list of point cloud research papers
- you are looking for benchmark datasets for 3D perception tasks
- you are starting research in 3D vision or autonomous driving perception

## When to avoid
- you need runnable software or a code library rather than a paper list
- you need production point cloud processing tools
- you need maintained code with a license for commercial use

## Facets
- artifact type: learning-resource
- maturity: active
- function: computer-vision, machine-learning
- domain: computer-vision, autonomous-vehicles, artificial-intelligence, awesome-lists
- platform: python, cross-platform
- tags: point-cloud, 3d-vision, papers, datasets, awesome-list, research

## Member repositories
- zhulf0804/3D-PointCloud (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:30.882411+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 2026-08-30T07:33:09.360824+00:00, confidence not recorded.
  - readme: https://github.com/zhulf0804/3D-PointCloud (fetched 2026-08-28T04:07:30.882411+00:00, sha ed33c89f79a7)
- Data as of 2026-08-30T08:39:29.467469+00:00.