PaperCodeResultsDateStars Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles 22 Dec 2021 103 Improving Object Detector Training on Synthetic Data by Starting With a Strong Baseline Methodology 30 May 2024 Previous 1 Next Showing 1 to 2 of 2 papers Dataset Loaders Edit ...
(CCDM2024) in Paris, France, for various core vision tasks on drone platform. To this end, we collect the large-scale drone-captured VisDrone2024 dataset with rich annotation and evaluate and discuss state-of-the-art algorithms. Besides, we will invite researchers to participate in challenges ...
Hello, I have a question about the paper submitition. If I want to submit a paper and have good results on serveral standard datasets, do I have to join your challenge and have results on visdrone dataset, or I just need to fit in one of your topics, for instance, people and object...
Conclusion This paper reviews the VisDrone-DET2019 Challenge and its results. A set of 47 detectors have been evaluated on the released dataset, 33 of which perform better than the strong baseline Cascade-RCNN [2] detector. The top three Table 3...
VisDrone-DatasetVisDrone-DatasetPublic The dataset for drone based detection and tracking is released, including both image/video, and annotations. 1.6k177 DroneVehicleDroneVehiclePublic Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning ...
aistudio:https://aistudio.baidu.com/aistudio/datasetdetail/1157293. ppyoloe介绍 ppyoloe是基于ppyolo做的一系列改进和升级,是单阶段Anchor-free模型,超越了多种流行的yolo模型,取得了最新的SOTA。 ppyoloe有一系列的模型,即s/m/l/x,可以通过width multiplier和depth multiplier配置。同时避免使用诸如deformable...
In this paper, we collect a new Multi-Drone single Object Tracking (MDOT) dataset that consists of 92 groups of video clips with 113,918 high resolution frames taken by two drones and 63 groups of video clips with 145,875 high resolution frames taken by three drones. Besides, two ...
Due to the large number of small objects and similar characteristics between the objects in the VisDrone dataset, the current model cannot extract more small-scale features. Therefore, this paper proposes a stronger feature extraction FasterRCNN (SFE-FasterRCNN) that advances a feature extraction ...
4 Conclusions This paper concludes the VisDrone-VDT2018 challenge, which focuses on two tasks, i.e., (1) video object detection, and (2) multi-object tracking. A large- scale video object detection and tracking dataset is released, which consists of 79 challenging sequences with 33, 366 ...
This paper reviews the VisDrone-DET2018 challenge and its results. The challenge contains a large-scale drone-based object detection dataset, including 8, 599 images (6, 471 for training, 548 for validation, and 1, 580 for testing) with rich annotations, including object bounding boxes, object...