Abstract: Remote sensing platforms provide crucial data for applications such as urban planning and traffic monitoring. However, detecting small objects remains challenging due to low resolution, ...
Abstract: Object detection is a fundamental computer vision task that simultaneously locates and categorizes objects in images and videos. It is utilized in various fields, such as autonomous driving, ...
Abstract: Source-Free Object Detection (SFOD) enables knowledge transfer from a source domain to an unsupervised target domain for object detection without access to source data. Most existing SFOD ...
Abstract: The loss function and feature extraction framework are essential parts of the algorithm design and significantly affect the accuracy of oriented object detection in remote sensing images.
Abstract: A crucial computer vision problem is person detection, but real-world challenges including crowded backgrounds, inconsistent lighting, and object occlusion require accurate and robust models ...
Abstract: Object detection in aerial imagery, particularly from unmanned aerial vehicles (UAVs) and remote sensing platforms, is crucial but faces significant challenges such as modality misalignment, ...
Abstract: In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse array of ...
Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...
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