Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

Multispectral image pairs can provide the combined information, making object detection
applications more reliable and robust in the open world. To fully exploit the different …

Infrared and visible image fusion aims to utilize the complementary information between the
two modalities to synthesize a new image containing richer information. Most existing works …

Cross-modality fusing complementary information of multispectral remote sensing image
pairs can improve the perception ability of detection algorithms, making them more robust …

Multispectral image pairs can provide complementary visual information, making pedestrian
detection systems more robust and reliable. To benefit from both RGB and thermal IR …

Infrared and visible image fusion aims to integrate comprehensive information from multiple
sources to achieve superior performances on various practical tasks, such as detection, over …

Multimodal object detection has attracted great attention in recent years since the
information specific to different modalities can complement each other and effectively …

Object detection with multimodal inputs can improve many safety-critical systems such as
autonomous vehicles (AVs). Motivated by AVs that operate in both day and night, we study …

Drone-based vehicle detection aims at detecting vehicle locations and categories in aerial
images. It empowers smart city traffic management and disaster relief. Researchers have …

Effective feature fusion of multispectral images plays a crucial role in multispectral object
detection. Previous studies have demonstrated the effectiveness of feature fusion using …