Point Cloud
PointCloudCorruptioncrossed_arm_point_clouds
Crossed Arm Point Clouds Dataset
This dataset contains 3D point cloud data captured from a LiDAR scanner for crossed arm classification in the context of robot magic trick performance.
Overview
This dataset was collected for training and evaluating the Crossed Arm Voxel Network (CAVN) architecture, a deep learning model designed for 3D point cloud classification in human-robot interaction magic performances. The data supports classification of human arm positions during… See the full description on the dataset page: https://huggingface.co/datasets/ahanjaya/crossed_arm_point_clouds.Colored_Point_Clouds
Colored point-cloud completion — PoinTr-protocol occlusions
Colored ground truth and occluded partial inputs for colored point-cloud completion,
built from textured ShapeNetCore meshes. Three categories, 599 models, 1797 partials.
What makes this different from the usual completion sets: the ground truth carries
per-point color sampled from the mesh texture, and it is de-speckled before sampling,
so the color is actually correct rather than plausible-looking.… See the full description on the dataset page: https://huggingface.co/datasets/eylulpelinkilic/Colored_Point_Clouds.PointCloudPeople
Dataset Card for PointCloudPeople
The use of light detection and ranging (LiDAR) sensor technology for people detection offers a significant advantage in terms of data protection. However, to design
these systems cost- and energy-efficiently, the relationship between the measurement data and final object detection output with deep neural networks (DNNs) has to be
elaborated. Therefore, we present an automatically labeled LiDAR dataset for person detection, with different… See the full description on the dataset page: https://huggingface.co/datasets/LukasPro/PointCloudPeople.libero-3d-scene-pointcloud
LIBERO 3D Whole-Scene Point-Cloud GT (sim, labeled)
Per-frame whole-scene 3D point cloud for the LIBERO benchmark, sampled directly
from every object's visual mesh (posed by the replayed MuJoCo state) — complete,
view-independent geometry. Every point carries an instance label, and a single
is_ooi flag marks the task's objects-of-interest, so relevant objects are
extracted with one key at training time.
Scene = task objects + fixtures + the gripper (robot arm/mount excluded).… See the full description on the dataset page: https://huggingface.co/datasets/Kit-Key/libero-3d-scene-pointcloud.climbing-holds-pointcloud
Rock Climb — Grasp-Taxonomy-Aware 3D Diffusion Policy
Trains a DP3-style point cloud diffusion policy conditioned on grasp type (crimp/sloper/pinch/jug)
to autonomously grasp climbing holds with a Franka arm + LEAP Hand.
Quick Start (Training Machine)
1. Clone the repo
git clone https://github.com/rumilog/rock-climb.git tele
cd tele
2. Create a Python environment
python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip
Install… See the full description on the dataset page: https://huggingface.co/datasets/rlogh/climbing-holds-pointcloud.