SEQUENTIAL FUSION FOR 3D OBJECT DETECTION

Techniques are provided for improving a perception processing pipeline for object detection that fuses image segmentation data (e.g., segmentation scores) with LiDAR points. The disclosed techniques are implemented using an architecture that accepts point clouds and images as input and estimates oriented 3D bounding boxes for all relevant object classes. In an embodiment, a method comprises: matching temporally, using one or more processors of a vehicle, points in a three-dimensional (3D) point cloud with an image; generating, using an image-based neural network, semantic data for the image; decorating, using the one or more processors, the points in the 3D point cloud with the semantic data; and estimating, using a 3D object detector with the decorated points as input, oriented 3D bounding boxes for the one or more objects.