3D object detection based on LiDAR point cloud and prior anchor boxes is a critical technology for autonomous driving environment perception and understanding.

In comparison to methods based on stereo cameras and lidar, monocular 3D object detection offers advantages such as a broad detection field and low deployment costs. However, the accuracy of existing ...

3D object detection is a fundamental task in scene understanding. Numerous research efforts have been dedicated to better incorporate Hough voting into the 3D object detection pipeline. However, due ...

Master thesis focuses on utilizing transfer learning techniques and object detection algorithms to analyze 3D LiDAR data, aiming to enhance the accuracy and efficiency of object recognition in ...

Graded projects of the course Deep Learning for Autonomous Driving, ETH Zürich (Spring 2021). Topics: Multi-task learning for semantics and depth, 3D Object Detection from Lidar Point Clouds. Master ...