VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results Dawei Du1, Pengfei Zhu2, Longyin Wen3, Xiao Bian4, Haibin Ling5, Qinghua Hu1, Tao Peng2, Jiayu Zheng2, Xinyao Wang3, Yue Zhang3, Liefeng Bo3, Hailin Shi...
object-detectiondisaster-managementyolov5drone-imagesyolov8yolov10 UpdatedMar 26, 2025 Jupyter Notebook mr-ravin/Aerial-Semantic-Segmentation-Drone-using-Pytorch Star1 Code Issues Pull requests This repository includes Pytorch implementation of semantic segmentation on aerial image of drone dataset. ...
Drone imageReceptive field expandedMultiscale feature fusionThe field of object detection in images captured by drones is witnessing a growing surge in research interest. However, because of the abundance of densely packed small objects in the majority of drone images, efficiently detecting dense small...
DroneDetection/README.md Hello! I am currently a Ph.D. candidate in Biomedical Engineering at the University of Electronic Science and Technology of China (UESTC). My research focuses on neuromorphic vision perception and small object detection, aiming to advance computational models that mimic ...
Table1shows the experimental results of various YOLO versions on the VisDrone2019-val dataset, including mAP, mAP, number of parameters (M), amount of computation (GFLOPs), and single-image inference speed (FPS). From the results in the table, it can be seen that SL-YOLO performs well in...
Object detection is a hot topic with various applications in computer vision, e.g., image understanding, autonomous driving, and video surveillance. Much of the progresses have been driven by the availability of object detection benchmark datasets, inclu
(1) objects are generally small in the image plane, blurred, and frequently occluded, making them challenging to detect and recognize; (2) drones move and see objects from different angles, causing the unreliability of the predicted positions and feature embeddings of the objects. This paper ...
Drone-based Object Counting by Spatially Regularized Regional Proposal Network ICCV2017数据库:https://lafi.github.io/LPN/ 本文主要使用CNN网络处理无人机拍摄的视频,同时完成对图像中的车辆检测和计数,新建了一个用无人机拍摄停车场的数据库 CARPK,含有近9万辆车 下面是一个示意图: ...
Contribute to VisDrone/Multi-Drone-Multi-Object-Detection-and-Tracking development by creating an account on GitHub.
Contribute to VisDrone/Multi-Drone-Multi-Object-Detection-and-Tracking development by creating an account on GitHub.