LAGSwin: Local attention guided Swin-transformer for thermal infrared sports object detection.

ABSTRACT: Compared with visible light images, thermal infrared images have poor resolution, low contrast, signal-to-noise ratio, blurred visual effects, and less information. Thermal infrared sports target detection methods relying on traditional convolutional networks capture the rich semantics in high-level features but blur the spatial details. The differences in physical information content and spatial distribution of high and low features are ignored, resulting in a mismatch between the region of interest and the target. To address these issues, we propose a local attention-guided Swin-transformer thermal infrared sports object detection method (LAGSwin) to encode sports objects' spatial transformation and orientation information. On the one hand, Swin-transformer guided by local attention is a

SUBMITTER: Meng H 

PROVIDER: S-EPMC11003622 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature