Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation
Researchers have developed a novel architecture for RGB-Thermal semantic segmentation, addressing challenges in adverse lighting conditions. The proposed method utilizes dual ConvNeXt V2 backbones with stage-wise, modality-adaptive fusion. It incorporates a Frequency-Based Fusion Module for early-stage features and a semantic fusion module with cross-modal attention for late-stage features, improving scene understanding by effectively integrating visible and infrared imagery. AI
IMPACT This research could lead to more robust computer vision systems for autonomous driving and other applications requiring scene understanding in challenging lighting conditions.