dsml-bryan's Stars
dotbts/BPA
Bike, Pedestrian, and Accessibility
Yarroudh/segment-lidar
Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.
facebookresearch/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
dvlab-research/SphereFormer
The official implementation for "Spherical Transformer for LiDAR-based 3D Recognition" (CVPR 2023).
OpenDroneMap/ODM
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
wangx1996/Fast-Ground-Segmentation-Based-on-JPC
An implementation on "Shen Z, Liang H, Lin L, Wang Z, Huang W, Yu J. Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process. Remote Sensing. 2021; 13(16):3239. https://doi.org/10.3390/rs13163239"
alexis-mignon/pygpmf
A python Module to extract GPMF information from Videos
mileyan/Pseudo_Lidar_V2
(ICLR) Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
hku-mars/livox_camera_calib
This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.
ialhashim/DenseDepth
High Quality Monocular Depth Estimation via Transfer Learning
xinge008/Cylinder3D
Rank 1st in the leaderboard of SemanticKITTI semantic segmentation (both single-scan and multi-scan) (Nov. 2020) (CVPR2021 Oral)
mit-han-lab/spvnas
[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
joedlopes/carla-simulator-multimodal-sensing
Vehicle Detection using Data Fusion and Multi-Task Learning. The models are trained using CARLA Simulator to generate Camera (RGB images) and LIDAR point cloud.
YuePanEdward/RoadMarkingExtraction
🛣️ automatic extraction of road markings from MLS or ALS point cloud [ISPRS-A' 19]
Lukas-Justen/Lane-Marking-Detection
This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.
Yochengliu/awesome-point-cloud-analysis
A list of papers and datasets about point cloud analysis (processing)
bmmeijers/grassfire
Grassfire - Straight skeleton by means of kinetic triangulation [Python]
cambridgegis/cambridgegis_data
City of Cambridge GIS Data
daavoo/pyntcloud
pyntcloud is a Python library for working with 3D point clouds.
wkentaro/labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
isl-org/Open3D-ML
An extension of Open3D to address 3D Machine Learning tasks
WeikaiTan/Toronto-3D
A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways
QingyongHu/RandLA-Net
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)
torch-points3d/torch-points3d
Pytorch framework for doing deep learning on point clouds.
danpaquin/coinbasepro-python
The unofficial Python client for the Coinbase Pro API
VachelHU/EvoNet
Time-Series Event Prediction with Evolutionary State Graph, WSDM 2021
IHTSDO/snomed-database-loader
Represent SNOMED CT in a different types of databases
ufbmi/icd-tools
OHDSI/Vocabulary-v5.0
Build process for the OHDSI Standardized Vocabularies. Currently not available as independent release.