Lightweight 2D Map Construction of Vehicle Environments Using a Semi-Supervised Depth Estimation Approach
This paper addresses the problem of constructing a real-time 2D map for driving scenes from a single monocular RGB image. We presented a method based on three neural networks (depth estimation, 3D object detection, and semantic segmentation). We proposed a depth estimation neural network architectur...
Main Authors: | Alexey Kashevnik, Ammar Ali |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-06-01
|
Series: | Engineering Proceedings |
Subjects: | |
Online Access: | https://www.mdpi.com/2673-4591/33/1/28 |
Similar Items
-
Monocular Depth and Velocity Estimation Based on Multi-Cue Fusion
by: Chunyang Qi, et al.
Published: (2022-05-01) -
Deep Learning-Based Monocular Depth Estimation Methods—A State-of-the-Art Review
by: Faisal Khan, et al.
Published: (2020-04-01) -
Monocular Depth Cues in Computer Vision Applications
by: Diego Cheda
Published: (2014-06-01) -
Deep Learning-Based Stereopsis and Monocular Depth Estimation Techniques: A Review
by: Somnath Lahiri, et al.
Published: (2024-01-01) -
Joint Soft–Hard Attention for Self-Supervised Monocular Depth Estimation
by: Chao Fan, et al.
Published: (2021-10-01)