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

• المؤلف الرئيسي: Geng, Yue
• مؤلفون آخرون: Wang Dan Wei
• التنسيق: Thesis-Master by Coursework
• اللغة: English
• منشور في: Nanyang Technological University 2022
• الموضوعات: Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/156769

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...