Multispectral pedestrian detection has shown great advantages under poor illumination
conditions, since the thermal modality provides complementary information for the color …

Because infrared images emphasize thermal targets while visible images provide a wealth
of textural information, fusing the two modal images improves the human perception of the …

The aim of infrared and visible image fusion is to obtain an integrated image that contains
obvious object information and high spatial resolution background information. The …

To achieve accurate and robust object detection in the real-world scenario, various forms of
images are incorporated, such as color, thermal, and depth. However, multimodal data often …

RGB-T salient object detection (SOD) has been developed rapidly and achieved excellent
results in recent years. However, some problems have not yet been solved. The current RGB …

At present, the mainstream visible pedestrian detector is easily affected by the ambient
lighting, the complex background, and the pedestrians distance. While the infrared images …

Effective fusion of complementary information captured by multi-modal sensors (visible and
infrared cameras) enables robust pedestrian detection under various surveillance situations …

Recent advances in machine-learning, especially in deep neural networks have significantly
accelerated the development and deployment of transport-oriented intelligent designs with …

A pedestrian detector that uses visible and thermal infrared image pairs as the input has
better detection performance than a detector that uses only visible image under challenging …

Multimodal information (eg, visible and thermal) can generate robust pedestrian detections
to facilitate around-the-clock computer vision applications, such as autonomous driving and …