datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Point-CacheThe datasets in this repository are used in the paper Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis.
Datasets
The folder structure of used datasets should be organized as follows.
/path/to/Point-Cache
|----data # placed in the same level as `runners`, `scripts`, etc.
|----modelnet_c
|----sonn_c
|----obj_bg
|----obj_only
|----hardest
|----modelnet40… See the full description on the dataset page: https://huggingface.co/datasets/auniquesun/Point-Cache.poi-benchmark
POI Benchmark: Multi-City Multimodal Points of Interest
A large-scale multimodal benchmark pairing Points of Interest (POIs) with street-view imagery, aerial grid photos, and satellite imagery across 10 major cities on 3 continents.
Cities
Beijing, Chengdu, Guangzhou, Hong Kong, Shanghai, Shenzhen, London, Melbourne, New York, Sydney.
Contents
Path
Size
Type
Description
metadata_aligned.tar
8.6 GB
11 JSON files
Enriched & aligned POI metadata per… See the full description on the dataset page: https://huggingface.co/datasets/sukiewang/poi-benchmark.cocoa_tree_point_cloud_segmented
Cocoa Tree Point Cloud Segmented
This dataset provides real LiDAR point cloud data of cocoa trees in a field environment in Cameroon, collected for crop segmentation applications within agroforestry systems. Captured using a ground-based Leica ScanStation C10 during August 2019, it delivers high-resolution structural information of cocoa tree canopies for agricultural monitoring research. The dataset contains 85 images across 3 classes: full, leaf, wood.Images per class:
full:… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/cocoa_tree_point_cloud_segmented.cocoa_tree_point_cloud
Cocoa Tree Point Cloud
This dataset provides real-world LiDAR point cloud data of cocoa trees cultivated within agroforestry systems in a field environment near Yorro, Cameroon. Collected using a ground-based Leica ScanStation C10 during August 2019, it captures detailed structural information of cocoa trees in their natural agricultural setting. The data supports research into crop segmentation and structural analysis of cocoa plantations using terrestrial LiDAR technology. The… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/cocoa_tree_point_cloud.