Unsupervised domain adaptation for depth completion from sparse LiDAR scans depth map

• Main Author: Geng, Yue
• Other Authors: Wang Dan Wei
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/156769
• Institution: Nanyang Technological University

Depth completion aims to predict the distance between objects on an image and the camera capturing the image from a LiDAR scans depth input, and the distance is expressed as a dense depth map. Denser scans depth input leads to better prediction, while the cost of the corresponding LiDAR equipment wi...