Pinned Repositories
3d_euclidean_cluster
3d_line_detection
3d line detection from pointcloud using Hough Transform
aiimooc_lesson
睿慕课三维点云处理课程作业代码
autoware.universe
BERT-keras
Keras implementation of BERT with pre-trained weights
bev_lane_det
BEVDet
Official code base of the BEVDet series .
BEVFormer
This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
ywfwyht's Repositories
ywfwyht/3d_euclidean_cluster
ywfwyht/3d_line_detection
3d line detection from pointcloud using Hough Transform
ywfwyht/aiimooc_lesson
睿慕课三维点云处理课程作业代码
ywfwyht/BERT-keras
Keras implementation of BERT with pre-trained weights
ywfwyht/camera_instrinsic_calibration
camera intrinsic calibration from (almost) scratch for better understanding of intrinsic calibration mechanism
ywfwyht/CenterPillarNet
An anchor free method for pointcloud object detecion.
ywfwyht/CenterPoint
Export CenterPoint PonintPillars ONNX Model For TensorRT
ywfwyht/CUDA-PointPillars
A project demonstrating how to use CUDA-PointPillars to deal with cloud points data from lidar.
ywfwyht/Lane-Detection-from-Point-Cloud
Detect lanes from the point cloud of a 80-meter highway road
ywfwyht/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.
ywfwyht/Large-scale_Point_Cloud_Semantic_Segmentation
ywfwyht/latte
LATTE: Accelerating LiDAR Point Cloud Annotation via Sensor Fusion, One-Click Annotation, and Tracking
ywfwyht/Lidar-Segementation
An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from IROS 2019
ywfwyht/lidar_camera_calibration_point_to_plane
Extrinsic Calibration of Monocular Camera and Lidar using Planar Point To Plane Constraint
ywfwyht/lidar_obstacle_detector
3D LiDAR Object Detection & Tracking using Euclidean Clustering, RANSAC, & Hungarian Algorithm
ywfwyht/mmdeploy
OpenMMLab Model Deployment Framework
ywfwyht/mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
ywfwyht/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
ywfwyht/patchwork
Official page of Patchwork (RA-L'21 w/ IROS'21)
ywfwyht/PINet_new
ywfwyht/Pointnet2.PyTorch
A PyTorch Implementation of Pointnet++.
ywfwyht/PyQt-Chinese-tutorial
PyQt6中文教程
ywfwyht/RangeNetTrt8
tensorrt8 && cuda && libtorch implementation of rangenet++
ywfwyht/ransac_lines_fitting_gpu
simple GPU ransac fitting of multiple lines on 2d/3d point cloud
ywfwyht/Road-boundary-edge-curb-detection
ywfwyht/semantic-segmentation-editor
Web labeling tool for bitmap images and point clouds
ywfwyht/SFA3D
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
ywfwyht/SparseConvNet
Submanifold sparse convolutional networks
ywfwyht/SUSTechPOINTS
3D Point Cloud Annotation Platform for Autonomous Driving
ywfwyht/torch2trt
An easy to use PyTorch to TensorRT converter