3D Object Detection Using Semantic Maps

In the proposed study, semantic maps were strategically integrated into LiDAR and RGB images to enhance object proposals for 3D detection. This integration involved fusing semantic information derived from the maps with corresponding points in the LiDAR data and RGB images. The effect of this integration was a noteworthy advancement in the precision and accuracy of object proposals. By enriching every point in the 3D point cloud data with semantic information, the model gained a more nuanced understanding of object classes and their spatial relationships. This enhanced comprehension contributes to more refined and contextually relevant object proposals, elevating the overall effectiveness of the 3D object detection system.