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project_ran
ilessio-aiflowlab/project_ran
project_ran is a machine learning model from ilessio-aiflowlab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Paper: OpenUrban3D (Wang et al., Sep 2025)
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Updated Apr 3, 2026
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.pth31.1 MB · 34%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Mar 28, 2026
- Updated
- Apr 3, 2026
- SHA
- 7a6f75ce
Datasets
Model card
From the Hugging Face model README
OpenUrban3D (RAN) — Annotation-Free Open-Vocabulary 3D Segmentation
Paper: OpenUrban3D (Wang et al., Sep 2025)
Architecture
- 3D Backbone: MinkUNet (sparse 3D convolutions)
- 2D Feature Extractor: ODISE (frozen)
- Text Encoder: CLIP ViT-L/14 (frozen)
- Training: Knowledge distillation (VL features → 3D backbone)
Usage
from anima_ran.inference.zero_shot import ZeroShotSegmenter
segmenter = ZeroShotSegmenter(backbone_checkpoint="pytorch/ran_v1.pth")
segmenter.load()
result = segmenter.segment(points, ["building", "vegetation", "road"])
Training Config
- Optimizer: Adam, LR=1e-4
- Epochs: 60, Batch size: 2
- Voxel size: 0.2m
- Hardware: 2x NVIDIA A6000
Citation
@article{wang2025openurban3d,
title={OpenUrban3D: Annotation-Free Open-Vocabulary Semantic Segmentation of Large-Scale Urban Point Clouds},
author={Wang, Chongyu and Jing, Kunlei and Zhu, Jihua and Wang, Di},
journal={arXiv preprint arXiv:2509.10842},
year={2025}
}
ANIMA Project
Part of the ANIMA Wave-6 multi-agent robotics perception system.
- License
- apache-2.0
- Created
- Mar 28, 2026
- Updated
- Apr 3, 2026