Search Results for "point cloud dataset"
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Showing 16 open source projects for "point cloud dataset"
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. -
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Habitat-Sim
A flexible, high-performance 3D simulator for Embodied AI research
...It offers GPU-accelerated rendering and a flexible sensor suite—RGB, depth, semantic segmentation, and more—so agents can perceive and act in realistic scenes. The engine is written in C++ with Python bindings and integrates physics, navigation meshes, and shortest-path planners to support tasks like point-goal navigation, rearrangement, and interactive manipulation. It ships with connectors to popular datasets and scene formats, plus tools for dataset generation and scene replay. Determinism and reproducibility are first-class goals, which is critical for benchmarking agents and comparing algorithms. Thanks to its speed and modular design, Habitat-Sim is widely used to prototype embodied agents, train at scale, and evaluate in standardized environments with consistent metrics. -
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Mesh R-CNN
code for Mesh R-CNN, ICCV 2019
Mesh R-CNN is a 3D reconstruction and object understanding framework developed by Facebook Research that extends Mask R-CNN into the 3D domain. Built on top of Detectron2 and PyTorch3D, Mesh R-CNN enables end-to-end 3D mesh prediction directly from single RGB images. The model learns to detect, segment, and reconstruct detailed 3D mesh representations of objects in natural images, bridging the gap between 2D perception and 3D understanding. Unlike voxel-based or point-based approaches, Mesh... -
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pyntcloud
pyntcloud is a Python library for working with 3D point clouds
This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. ... -
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Frappe Charts
Simple, responsive, modern SVG Charts with zero dependencies
GitHub-inspired simple and modern SVG charts for the web with zero dependencies. An axis chart is generally a 2D rendition of data, where a set of values corresponds to every point in a dataset. That's why, data is the most important component for a chart. A chart can have multiple datasets. In an axis chart, every dataset is represented individually. Frappe Charts are responsive, as they rerender all the data in the current available container width. In order to set the bar width, instead of defining it and the space between the bars independently, we simply define the ratio of the space between bars to the bar width. ... -
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generativeart
Create Generative Art with R
generativeart is an R package for creating algorithmic art by computing the positions of many thousands of points according to user-defined mathematical formulas with randomized parameters. Each render uses a seed to introduce controlled randomness, so every image is unique while remaining reproducible when the same seed and formula are reused. The package logs the seed, formula, and file name to a CSV, which makes it easy to catalog outputs, re-generate favorites, and track experiments. A... -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. ... -
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hubs-research-acm-chi-2021
Supplemental code and dataset for the ACM CHI 2021 paper
Supplemental code and dataset for the ACM CHI 2021 paper on "Proxemics and Social Interactions in an Instrumented Virtual Reality Workshop". In this research paper we instrumented Mozilla Hubs Cloud to record where participants where during the event. From there, we measured proxemic and plotted the activity along with some semi-structured interviews. Virtual environments (VEs) can create collaborative and social spaces, which are increasingly important in the face of remote work and travel reduction. ... -
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
...This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few commands. When training your own model, start with only PSNR loss (50+ epochs, depending on the dataset) and only then introduce GANS and feature loss. This can be controlled by the loss weights argument. The weights used to produce these images are available directly when creating the model object. ... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured... -
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Point Cloud Skinner for Blender
Python script (addon) for Blender to skin point cloud (verts to face).
...Features: This script, Point Cloud Skinner can skin a cloud of vertices, which means to create a 3D surfaced mesh out of just a cloud of vertices that has no faces. It can skin any shapes of point clouds, such as a surveyed geography point cloud that represents a landform somewhere, a fluid volumetric point cloud obtained by numerical fluid simulation, or anything you like. -
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Manifold mesh processing
Mesh and point cloud processing tools
A suite of tools for processing and analyzing meshes and point clouds. 1) Ensuring that meshes are manifold, ie, "nice" 2) Simple smoothing/noise reduction 3) Bare-bones point cloud to mesh and robust normals for point clouds 4) Mesh simplification 5) Curvature calculation on meshes 6) Local shape descriptors on meshes -
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Point Cloud Library
Standalone, large scale, open project for 3D point cloud processing.
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. We are financially supported by Open Perception, Willow Garage, NVIDIA, Google, Toyota, Trimble, Urban Robotics, Honda Research Institute, Sandia, Dinast, Optronic, Ocular Robotics, Velodyne, Fotonic, Leica Geosystems, and MKE. -
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ZPR is a program that produces orthophotos. The method used is to give colors to point-cloud (photo obtained by a digital camera, cloud obtained by a laser scanner) and to project the point-cloud to a requested plane. With this method, the projection pla
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Open source point cloud viewer forked from Radiohead House of Cards Project, based on the Processing Programming Language.
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PhotoCloud is a tool to browse and a navigate for datasets composed of (a) a collection of registered images and (b) a 3D model over which images are aligned. The 3D model can be a point-cloud, triangle mesh. PhotoCloud is based on a client/server architecture and it is scalable: very large dataset (both in terms of (a) and (b) can be handled.
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