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Title: A Critical Review of Deep Learning-Based Multi-Sensor Fusion Techniques
Authors: Marsh, B
Sadka, AH
Bahai, H
Keywords: sensor fusion;stereo;LiDAR;deep learning
Issue Date: 1-Dec-2022
Publisher: MDPI
Citation: Marsh B. et. al.(2022) 'A Critical Review of Deep Learning-Based Multi-Sensor Fusion Techniques', Sensors, 22 (23), 9364, pp.1-19. doi: 10.3390/s22239364.
Abstract: In this review, we provide a detailed coverage of multi-sensor fusion techniques that use RGB stereo images and a sparse LiDAR-projected depth map as input data to output a dense depth map prediction. We cover state-of-the-art fusion techniques which, in recent years, have been deep learning-based methods that are end-to-end trainable. We then conduct a comparative evaluation of the state-of-the-art techniques and provide a detailed analysis of their strengths and limitations as well as the applications they are best suited for.
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