The field of vehicle detection and 3D object recognition is moving towards more accurate and efficient methods, leveraging advancements in computer vision and machine learning. Researchers are exploring the use of drone videos, camera-based methods, and 3D point cloud data to improve vehicle speed detection, axle classification, and object detection. Noteworthy papers include one that proposes a fine-tuned YOLOv11 model for vehicle speed detection with high accuracy, and another that introduces a novel reconstruction-free online framework for 3D object detection via real-time multi-view box fusion. Overall, the field is advancing towards more robust and real-time capable systems, enabling safer and more efficient transportation systems.