Semantic-Aware Dynamic Feature Selection and Fusion for Object Detection in UAV Videos

Jianping Zhong, Zhaobo Qi, Weigang Zhang, Qingming Huang

Abstract: Keypoint-based detectors perform well in surveillance videos but face challenges in detecting objects in UAV videos due to missed corners and mismatches. To address this, we propose a semantic-aware module with a feature fusion sub-module and a feature selection sub-module. The feature fusion module adaptively combines low-level and high-level features, enhancing corner recall. The feature selection module determines spatial location importance, improving discriminative capabilities and reducing background interference, resulting in better precision. Experiments on the UAVDT benchmark show our method achieves competitive results. Notably, our method improves corner recall by 4.0% and reduces the mismatch rate by 2.9% compared to the baseline. Code is available at https://github.com/jianpingZhonggit/SemanticAwareModule.