The authors of the UAVOD-10: 10 category UAV Small Weak Object Detection Dataset address the growing potential of imaging sensors utilized in remote sensing to capture high-resolution images that reveal intricate details of the Earth’s surface. This advancement allows for the detection of small-scale and weak-feature-response geospatial targets, a task of considerable importance in various applications. While existing efforts in small weak object detection predominantly center around processing satellite images, the authors recognized the significance of unmanned aerial vehicle (UAV) remote sensing images, which possess exceptionally high resolutions and shorter revisit intervals. Despite their potential, UAV images present unique challenges such as high intra-class variations, complex contexts, and noise, which have received relatively less attention.

To facilitate the remote sensing detection of small weak objects in UAV images, the authors introduced a new 10-category UAV object detection dataset termed UAVOD-10. This dataset encompasses diverse objects influenced by imaging conditions and contexts, with some objects exhibiting small scales and weak feature responses, making them particularly challenging to discern. To address these complexities, the authors proposed a context-scale-aware detector named CSADet. This detector incorporates a context-aware module for joint exploration of local and global contexts, along with a multi-scale feature refinement module for comprehensive feature extraction and sharing.

The authors emphasized the significance of small weak object detection in real-world scenarios, where geospatial objects often appear only partially within UAV images due to the distance between sensors and objects. This introduces challenges related to scale variations, complex backgrounds, and imaging conditions. Existing general-purpose detectors were deemed inadequate for such specific applications, necessitating the creation of a specialized dataset like UAVOD-10. This dataset is designed to address the limitations of existing datasets by encompassing a wider range of object categories, appearance variations, shadows, occlusions, and noise.

To address these challenges, CSADet was developed to effectively detect small weak objects in UAV images by leveraging context information and multiscale feature extraction. The proposed method demonstrated improved accuracy, as indicated by experimental results on the UAVOD-10 dataset. The authors’ contributions encompass the creation of a comprehensive UAVOD-10 dataset, the development of the CSADet detector, and the systematic evaluation of their combined effectiveness, showcasing improvements in detection accuracy.

The UAVOD-10 dataset comprises 844 images and a total of 18,234 instances, each annotated with horizontal bounding boxes (HBBs). The images exhibited widths ranging from 1000 to 4800 pixels, with an approximate resolution of 0.15 meters. Analysis of the dataset revealed class imbalance, where certain classes such as buildings and prefabricated houses were well-represented, while others like quarries, pools, and landslides had fewer instances. Objects within the same or different categories exhibited distinct scale differences. The smallest building instance had a width of 9 pixels, while the largest measured 312 pixels, with an average width of 74.85 pixels. Other classes like quarry, pool, and landslide displayed larger average widths and standard deviations, aligning with real-world scenarios.

The authors of the dataset meticulously selected geospatial target categories to curate UAVOD-10. Utilizing a mountainous region in Liuzhi Special Economic Zone, Guizhou Province, China, as the study area, the authors identified ten classes of targets: building, prefabricated house, ship, well, cable tower, vehicle, cultivation mesh cage, quarry, pool, and landslide. This selection encompassed common targets present in high-resolution remote sensing (HRRS) datasets, alongside novel categories like well and cable tower, which aligned with the authors’ definition of small weak objects susceptible to occlusion and lighting conditions. Additionally, the authors included landslide, mesh cultivation cage, and quarry as research targets, addressing objects rarely explored in existing works despite not being small weak objects.