LiDAR Perception Task

LiDAR perception tasks involve extracting meaningful information from LiDAR point cloud data for applications like autonomous driving. Current research focuses on developing unified multi-task networks, often employing transformer architectures, to simultaneously perform tasks such as 3D object detection, semantic segmentation, and panoptic segmentation, improving efficiency and performance compared to separate models. These advancements are driven by the need for robust and accurate scene understanding, impacting the development of safer and more reliable autonomous systems and advancing the field of 3D computer vision. The creation of large-scale, diverse datasets for cross-domain evaluation is also a key area of focus.