icip2022 paper: sahi benchmark on visdrone and xview datasets using fcos, vfnet and tood detectors
ECCV2018(Challenge-Object Detection in Images)
VisDrone aerial object detection toolkit with 33 models (Torchvision + YOLO), training, evaluation, video inference, benchmarking, and annotation conversion.
Many yolov8 model are trained on the VisDrone dataset.
YOLO-TLP: detected and classified tiny objects with bounding box dimensions smaller than 15 pixels, outperforming other one-stage detectors. maximum resolution for target observation in real-time applications.
Simple implement of CenterNet on VisDrone dataset.
Small Object Detection in Dense UAV Imagery using YOLOv8-L with Structured Ablation (EMA, P2 Head, PIoU) and SAHI Evaluation on VisDrone2019.
dataset or annotation file format conversion
An end-to-end computer vision system for aerial imagery, implemented and validated on a commercial drone for real-time video inference
Object Detection on the Visdrone dataset
Research Implementation for small-object detection in UAV imagery, combining Partial Convolution C2f, Attention-Guided FPN, a P2 detection head, and Wise-IoU v3. Evaluated on VisDrone-DET2019, it studies whether independently validated techniques remain effective when combined.
UAV aerial object detection and tracking (YOLOv8n + SORT) on VisDrone Dataset, with ONNX FP32/INT8 export and CPU deployment benchmarking.
Small object detection on VisDrone with YOLOv11s + SAHI
北斗 + 改进 YOLOv8m 的小目标识别辅助系统：EMA 注意力 / DySample / DualConv / Slim-Neck / NWD 损失 / P2 分支，面向 VisDrone2019-DET。
Object detection format converter from VisDrone2019-DET to Yolo.
Vehicle Detection using YOLOv26 trained on VisDrone dataset for detecting cars,vans,trucks and buses
Reproducible VisDrone benchmark scaffold for CNN, DETR, Vision Mamba, and RT-DETR families.
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