ERA: A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos
Along with the increasing use of unmanned aerial vehicles (UAVs), large volumes of aerial videos have been produced. It is unrealistic for humans to screen such big data and understand their contents. Hence methodological research on the automatic understanding of UAV videos is of paramount importance. In this paper, we introduce a novel problem of event recognition in unconstrained aerial videos in the remote sensing community and present a large-scale, human-annotated dataset, named ERA (Event Recognition in Aerial videos), consisting of 2,864 videos each with a label from 25 different classes corresponding to an event unfolding 5 seconds. The ERA dataset is designed to have a significant intra-class variation and inter-class similarity and captures dynamic events in various circumstances and at dramatically various scales. Moreover, to offer a benchmark for this task, we extensively validate existing deep networks. We expect that the ERA dataset will facilitate further progress in automatic aerial video comprehension. The website is https://lcmou.github.io/ERA_Dataset/
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
MOR-UAV: A Benchmark Dataset and Baselines for Moving Object Recognition in UAV Videos
Visual data collected from Unmanned Aerial Vehicles (UAVs) has opened a new frontier of computer vision that requires automated analysis of aerial images/videos. However, the existing UAV datasets primarily focus on obje…
Objectobject-detectionObject DetectionObject RecognitionHuman Action Recognition in Drone Videos using a Few Aerial Training Examples
Drones are enabling new forms of human actions surveillance due to their low cost and fast mobility. However, using deep neural networks for automatic aerial action recognition is difficult due to the need for a large nu…
Action ClassificationAction RecognitionTemporal Action LocalizationCross-Task Transfer for Geotagged Audiovisual Aerial Scene Recognition
Aerial scene recognition is a fundamental task in remote sensing and has recently received increased interest. While the visual information from overhead images with powerful models and efficient algorithms yields consid…
Scene RecognitionJoint Inference of Groups, Events and Human Roles in Aerial Videos
With the advent of drones, aerial video analysis becomes increasingly important; yet, it has received scant attention in the literature. This paper addresses a new problem of parsing low-resolution aerial videos of large…
Anomaly Detection in Aerial Videos with Transformers
Unmanned aerial vehicles (UAVs) are widely applied for purposes of inspection, search, and rescue operations by the virtue of low-cost, large-coverage, real-time, and high-resolution data acquisition capacities. Massive …
Anomaly Detection