SSZ1
Ph.D. candidate in LIESMARS, Wuhan University. Research Interests: Computer Vision and Deep Learning, UAV, Image and Point cloud intelligent processing.
LIESMARS, Wuhan UniversityWuhan，China
Pinned Repositories
3D-Machine-Learning
A resource repository for 3D machine learning
A-LOAM
Advanced implementation of LOAM
asoom_oss
Open Source Release of ASOOM
ComfyUI-YoloWorld-EfficientSAM
Unofficial implementation of YOLO-World + EfficientSAM for ComfyUI
CropImageandJsonfromLABELME
Process the semantic segmentation mask labels files（json type）from Labelme for Instance segmentation training on PolarMaks
CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
DynamicDet
[CVPR 2023] DynamicDet: A Unified Dynamic Architecture for Object Detection
Fast-Drone-250
hardware and software design of the 250mm autonomous drone
flightmare
An Open Flexible Quadrotor Simulator
SSZ1's Repositories
SSZ1/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
SSZ1/3D-Machine-Learning
A resource repository for 3D machine learning
SSZ1/asoom_oss
Open Source Release of ASOOM
SSZ1/ComfyUI-YoloWorld-EfficientSAM
Unofficial implementation of YOLO-World + EfficientSAM for ComfyUI
SSZ1/CropImageandJsonfromLABELME
Process the semantic segmentation mask labels files（json type）from Labelme for Instance segmentation training on PolarMaks
SSZ1/DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
SSZ1/DynamicDet
[CVPR 2023] DynamicDet: A Unified Dynamic Architecture for Object Detection
SSZ1/Fast-Drone-250
hardware and software design of the 250mm autonomous drone
SSZ1/flightmare
An Open Flexible Quadrotor Simulator
SSZ1/Grounded-Segment-Anything
Marrying Grounding DINO with Segment Anything & Stable Diffusion & BLIP - Automatically Detect , Segment and Generate Anything with Image and Text Inputs
SSZ1/IPC
Integrated Planning and Control for Quadrotor Navigation in Presence of Sudden Crossing Objects and Disturbances
SSZ1/Onboard-SDK-ROS
Official ROS packages for DJI onboard SDK.
SSZ1/Point-LIO
SSZ1/pytorch-book
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
SSZ1/pytorch3d
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
SSZ1/WindowTop
Set window on top, make it dark, transparent and more
SSZ1/FUEL
An Efficient Framework for Fast UAV Exploration
SSZ1/ImMesh
ImMesh: An Immediate LiDAR Localization and Meshing Framework
SSZ1/MCMOT
Real time one-stage multi-class & multi-object tracking based on anchor-free detection and ReID
SSZ1/Multimodal-Detection-and-Tracking-UAV
A Multimodal Detection and Tracking System based on DJI Payload SDK and Mobile SDK.
SSZ1/OpenPCDet
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
SSZ1/Paddle3D
A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.
SSZ1/PaddleSeg
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.
SSZ1/pytorch-handbook
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
SSZ1/r3live
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
SSZ1/RACER
Rapid Exploration with Multiple Unmanned Aerial Vehicles (UAV)
SSZ1/RT-DETR
[CVPR 2024] Official RT-DETR (RTDETR paddle pytorch), Real-Time DEtection TRansformer, DETRs Beat YOLOs on Real-time Object Detection. 🔥 🔥 🔥
SSZ1/Segment-and-Track-Anything
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.
SSZ1/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.
SSZ1/UAV_Path_Planning
single UAV's path planning using Lidar