{"adoption": {"forks": 336, "observed_at": "2026-08-28T04:05:03.614261+00:00", "stars": 1560}, "canonical_url": "https://ross.abutalabs.com/products/randla-net", "card": {"archived": false, "artifact_type": "library", "description": "🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)", "domain": ["computer-vision", "machine-learning", "deep-learning"], "enriched": true, "function": ["machine-learning", "deep-learning", "computer-vision"], "health_score": 20, "homepage": null, "language": "Python", "license": "NOASSERTION", "license_family": "other", "maturity": "maintenance", "member_repos": ["QingyongHu/RandLA-Net"], "name": "QingyongHu/RandLA-Net", "platform": ["python"], "pushed_at": "2023-07-11T22:42:23+00:00", "repo": "QingyongHu/RandLA-Net", "stars": 1560, "tags": ["point-clouds", "semantic-segmentation", "tensorflow", "cvpr-2020", "3d-vision", "research-code", "linux", "gpu"], "topics": ["semantic-segmentation", "3d-vision", "computer-vision", "semantic3d", "s3dis", "semantickitti"], "urls": [], "use_cases": ["segment large-scale 3d point clouds semantically", "run semantic segmentation on semantickitti dataset", "evaluate point cloud segmentation on s3dis benchmark", "reproduce cvpr 2020 randla-net results", "get pre-trained model for 3d lidar scene labeling", "benchmark efficient point cloud segmentation architectures"], "what_it_is": "Official TensorFlow implementation of RandLA-Net, a neural architecture for efficient semantic segmentation of large-scale 3D point clouds, published at CVPR 2020 (Oral) and IEEE TPAMI 2021. It includes training and evaluation scripts for benchmarks like S3DIS, Semantic3D, and SemanticKITTI with pre-trained models available.", "when_to_avoid": ["you need PyTorch or modern TensorFlow 2.x support", "you require a permissively licensed model for commercial use (CC BY-NC-SA 4.0)", "you need actively maintained code with recent dependency updates", "your project involves 2D image segmentation rather than 3D point clouds"], "when_to_choose": ["you need efficient semantic segmentation of large-scale 3D point clouds", "you want to reproduce or build on the RandLA-Net paper results", "you work with benchmarks like S3DIS, Semantic3D, or SemanticKITTI", "you need a lightweight point cloud segmentation model without heavy sampling or preprocessing"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/randla-net", "repo": "QingyongHu/RandLA-Net", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:05:03.614261+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:29:46.099881+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "3d53b76340c9fd02ee47c70406ee1548c3d17a804da760865b27fc19dc0963f2", "fetched_at": "2026-08-28T04:05:03.614261+00:00", "kind": "readme", "missing": false, "url": "https://github.com/QingyongHu/RandLA-Net"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2473, "days_push": 1149, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}