Pinned Repositories
apls
Python code to evaluate the APLS metric
Autodrive-3D-detection
Group project in HKUST
building_damage_detection
Code for building damage detection with xBD dataset.
CameraRadarFusionNet
Change-Detection-Review
A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.
CMU_Lidar_Navigation
CMU_UNet_Node
GAOFEN2021_CHANGEDETECTION
第五届中科星图杯高分辨率可见光图像中建筑物普查与变化检测
mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
Paper_Notes
lyp19's Repositories
lyp19/GAOFEN2021_CHANGEDETECTION
第五届中科星图杯高分辨率可见光图像中建筑物普查与变化检测
lyp19/mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
lyp19/Paper_Notes
lyp19/apls
Python code to evaluate the APLS metric
lyp19/Autodrive-3D-detection
Group project in HKUST
lyp19/building_damage_detection
Code for building damage detection with xBD dataset.
lyp19/CameraRadarFusionNet
lyp19/Change-Detection-Review
A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.
lyp19/CMU_Lidar_Navigation
lyp19/CMU_UNet_Node
lyp19/CurveLanes
CurveLanes is a new benchmark lane detection dataset with 150K lanes images for difficult scenarios such as curves and multi-lanes in traffic lane detection. It is collected in real urban and highway scenarios in multiple cities in China.
lyp19/ever
Earth Vision Foundation
lyp19/ICCV-Papers
lyp19/Image-Matching-Paper-List
A personal list of papers and resources of image matching and pose estimation, including perspective images and panoramas.
lyp19/img-match
lyp19/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.
lyp19/Learning-Deep-Learning
Paper reading notes on Deep Learning and Machine Learning
lyp19/leetcode-master
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
lyp19/livox_lane_detection
lyp19/nuscenes-devkit
The devkit of the nuScenes dataset.
lyp19/nuscenes-to-osm-exporter
NuScenes Map to OpenStreetMap Exporter
lyp19/pointcloud-landmarks-extractor
Tools to detect and classify landmarks (currently, trees and pole-like objects) from point cloud data
lyp19/resume
个人中文简历 Latex 源码 https://hijiangtao.github.io/
lyp19/RoadMarkingExtraction
A C++ Program for automatically extraction of road markings from MLS or ALS point cloud [ISPRS-A' 19]
lyp19/satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
lyp19/second.pytorch
SECOND for KITTI/NuScenes object detection
lyp19/slideslive-slides-dl
slideslive slides downloading script
lyp19/Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
lyp19/Transformer_nlp
lyp19/xView2_baseline
Baseline localization and classification models for the xView 2 challenge.