RGB-thermal (RGB-T) semantic segmentation enables intelligent vehicles to understand environments while operating in urban scenes. However, the research encounters two main challenges: 1) scarcity of training samples under snowy conditions and 2) challenge in applying the model in practice. To address the first challenge, we proposed a publicly accessible RGB-T semantic segmentation dataset in snowy urban scenes (SUS dataset). The SUS dataset comprises 1035 pairs of precisely registered RGB-T images, and provides pixel-level semantic annotations for five categories for all images. To tackle the second challenge, we introduced MCNet-S ${}^{\ast }$ , a novel semantic segmentation model that leverages knowledge distillation (KD). The KD structure consists of an RGB-T teacher model, named MCNet-T, and an RGB student model, named MCNet-S. Within MCNet-T, we proposed a cross-modal dual association (CDA) module to enhance utilization of RGB-T information in snowy urban scenes. Within MCNet-S, a depth-wise separable pyramid (DSP) module was proposed to improve the efficiency of RGB information utilization and align the feature dimensions with those of MCNet-T. Between MCNet-S and MCNet-T, memory-based contrastive learning distillation (MCLD) was proposed to transfer the prior thermal knowledge, improving the segmentation accuracy of MCNet-S and obtaining optimized MCNet-S $\ast $ . Extensive experiments on the SUS and MFNet datasets show that the proposed models outperform state-of-the-art models. The SUS dataset and codes are available at https://github.com/xiaodonguo/SUS_dataset.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Transferring Prior Thermal Knowledge for Snowy Urban Scene Semantic Segmentation


    Contributors:
    Guo, Xiaodong (author) / Liu, Tong (author) / Mou, Yefeng (author) / Chai, Siyuan (author) / Ren, Bohan (author) / Wang, Yijin (author) / Shi, Wei (author) / Liu, Siyuan (author) / Zhou, Wujie (author)


    Publication date :

    2025-08-01


    Size :

    2935463 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    An Evaluation of RGB-Thermal Image Segmentation for Snowy Road Environment

    Vachmanus, Sirawich / Ravankar, Ankit A. / Emaru, Takanori et al. | British Library Conference Proceedings | 2021


    Semantic video scene segmentation and transfer

    Gritti, T. / Damkat, C. / Monaci, G. | British Library Online Contents | 2014


    Speed Management on Icy and Snowy Pavement of Urban Road

    Wu, Li Xin ;Cheng, Guo Zhu | Trans Tech Publications | 2011


    SNOWY ROAD CRAWLER 2

    SATO YOSHIKAZU | European Patent Office | 2017

    Free access