Researchers are developing various approaches to improve vehicle and pedestrian detection in adverse weather conditions. These methods include the use of multi-dimensional attention transformers, hybrid attention and multi-scale fusion, and cross-modality feature fusion. The goal of these techniques appears to be enhancing the reliability of object detection in challenging environments, potentially for applications such as autonomous driving.