Efficient 3D Perception for Autonomous Vehicles
Offered By: MIT HAN Lab via YouTube
Course Description
Overview
Explore cutting-edge advancements in efficient 3D perception for autonomous vehicles in this invited talk from the CVPR 2023 ECV Workshop. Delve into BEVFusion, a groundbreaking approach that unifies camera, LiDAR, and radar features in a shared bird's-eye view space, accelerating multi-task multi-sensor fusion by 40 times. Discover how this leading solution achieves top performance across popular 3D perception benchmarks for tasks such as object detection, tracking, and map segmentation. Learn about FlatFormer, an efficient point cloud transformer that enables real-time performance on edge GPUs, and SparseViT, which leverages spatial sparsity in 2D image transformers for improved speed without sacrificing accuracy. Gain insights into the latest research addressing the efficiency challenges in autonomous vehicle perception, paving the way for real-world applications.
Syllabus
Efficient 3D Perception for Autonomous Vehicles (Zhijian Liu @ CVPR 2023 ECV)
Taught by
MIT HAN Lab
Related Courses
Getting started with Augmented RealityInstitut Mines-Télécom via Coursera Deep Learning in Computer Vision
Higher School of Economics via Coursera Computer Vision
Nvidia Deep Learning Institute via Udacity Computer Vision - Object Tracking with OpenCV and Python
Coursera Project Network via Coursera Python for Computer Vision with OpenCV and Deep Learning
Udemy