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Multi-Modal Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation

Alshammari, N.; Akcay, S.; Breckon, T.P.

Authors

N. Alshammari

S. Akcay



Abstract

Robust semantic scene segmentation for automotive applications is a challenging problem in two key aspects: (1) labelling every individual scene pixel and (2) performing this task under unstable weather and illumination changes (e.g., foggy weather), which results in poor outdoor scene visibility. Such visibility limitations lead to non-optimal performance of generalised deep convolutional neural network-based semantic scene segmentation. In this paper, we propose an efficient endto-end automotive semantic scene understanding approach that is robust to foggy weather conditions. As an end-to-end pipeline, our proposed approach provides: (1) the transformation of imagery from foggy to clear weather conditions using a domain transfer approach (correcting for poor visibility) and (2) semantically segmenting the scene using a competitive encoderdecoder architecture with low computational complexity (enabling real-time performance). Our approach incorporates RGB colour, depth and luminance images via distinct encoders with dense connectivity and features fusion to effectively exploit information from different inputs, which contributes to an optimal feature representation within the overall model. Using this architectural formulation with dense skip connections, our model achieves comparable performance to contemporary approaches at a fraction of the overall model complexity.

Citation

Alshammari, N., Akcay, S., & Breckon, T. (2021). Multi-Modal Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation.

Conference Name IEEE Intelligent Transportation Systems Society
Acceptance Date Apr 23, 2021
Online Publication Date Jul 11, 2021
Publication Date 2021-07
Deposit Date May 23, 2021
Publicly Available Date Mar 29, 2024
Publisher Institute of Electrical and Electronics Engineers
Publisher URL https://breckon.org/toby/publications/papers/alshammari21multimodal.pdf