[1] Wujie ZHOU, Jinfu LIU, Jingsheng LEI et al. GMNet: graded-feature multilabel-learning network for RGB-thermal urban scene semantic segmentation. IEEE Transactions on Image Processing, 30, 7790-7802(2021).
[2] Zhanxiang FENG, Jianhuang LAI, Xiaohua XIE. Learning modality-specific representations for visible-infrared person re-identification. IEEE Transactions on Image Processing, 29, 579-590(2020).
[3] Ying SUN, Zhiqiang HOU, Chen YANG et al. Object detection algorithm based on dual-modal fusion network. Acta Photonica Sinica, 52, 0110002(2023).
[4] Hui DENG, Changlong WANG, Yongjiang HU et al. Fusion of infrared and visible images based on non-subsampled dual-tree complex contourlet and adaptive block. Acta Photonica Sinica, 48, 0710006(2019).
[5] Zetao JIANG, Qi JIANG, Yongsong HUANG et al. Infrared and low-light-level visible light enhancement image fusion method based on latent low-rank representation and composite filtering. Acta Photonica Sinica, 49, 0410001(2020).
[6] Chenyang LI, Kun DING, Shuai WENG et al. Image fusion of infrared and visible images based on residual significance. Infrared Technology, 42, 1042-1047(2020).
[7] Weiwei KONG, Yang LEI, Huaixun ZHAO. Adaptive fusion method of visible light and infrared images based on non-subsampled shearlet transform and fast non-negative matrix factorization. Infrared Physics & Technology, 67, 161-172(2014).
[8] Zhishe WANG, Fengbao YANG, Zhihao PENG et al. Multi-sensor image enhanced fusion algorithm based on NSST and top-hat transformation. Optik-International Journal for Light and Electron Optics, 126, 4184-4190(2015).
[9] Hui LI, Xiaojun WU. Densefuse: a fusion approach to infrared and visible images. IEEE Transactions on Image Processing, 28, 2614-2623(2019).
[10] Zhishe WANG, Yuanyuan WU, Junyao WANG et al. Res2Fusion: infrared and visible image fusion based on dense Res2net and double non-local attention models. IEEE Transactions on Instrumentation and Measurement, 71, 1-12(2022).
[11] Zhishe WANG, Junyao WANG, Yuanyuan WU et al. UNFusion: a unified multi-scale densely connected network for infrared and visible image fusion. IEEE Transactions on Circuits and Systems for Video Technology, 32, 3360-3374(2022).
[12] Han XU, Jiayi MA, Junun JIANG et al. U2fusion: a unified unsupervised image fusion network. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 502-518(2022).
[13] Hui LI, Xiaojun WU, J KITTLER. RFN-Nest: an end-to-end residual fusion network for infrared and visible images. Information Fusion, 73, 72-86(2021).
[14] Linfeng TANG, Jiteng YUAN, Hao ZHANG et al. PIAFusion: a progressive infrared and visible image fusion network based on illumination aware. Information Fusion, 83-84, 79-72(2022).
[15] Jiayi MA, Wei YU, Pengwei LIANG et al. FusionGAN: a generative adversarial network for infrared and visible image fusion. Information Fusion, 48, 11-26(2019).
[16] Jiayi MA, Hang ZHANG, Zhenfeng SHAO et al. GANMcC: a generative adversarial network with multiclassification constraints for infrared and visible image fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 70, 1-14(2021).
[17] Zhishe WANG, Wenyu SHAO, Yanlin CHEN et al. Infrared and visible image fusion via interactive compensatory attention adversarial learning. IEEE Transactions on Multimedia, 25, 7800-7813(2023).
[18] Zhishe WANG, Wenyu SHAO, Yanlin CHEN et al. A cross-scale iterative attentional adversarial fusion network for infrared and visible images. Transactions on Circuits and Systems for Video Technology, 33, 3677-3688(2023).
[19] Zhishe WANG, Wenyu SHAO, Fengbao YANG et al. Infrared and visible image fusion method via interactive attention-based generative adversarial network. Acta Photonica Sinica, 51, 0410002(2022).
[20] Zhishe WANG, Yanlin CHEN, Wenyu SHAO et al. SwinFuse: a residual swin transformer fusion network for infrared and visible images. IEEE Transactions on Instrumentation and Measurement, 71, 1-12(2022).
[21] Wei TANG, Fazhi HE, Yu LIU. YDTR: infrared and visible image fusion via Y-shape dynamic transformer. IEEE Transactions on Multimedia, 25, 5413-5428(2023).
[22] Jiayi MA, Linfeng TANG, Fan FAN et al. SwinFusion: cross-domain long-range learning for general image fusion via swin transformer. IEEE/CAA Journal of Automatica Sinica, 7, 1200-1217(2022).
[24] Jinyuan LIU. M3FD database. https://github.com/dlut-dimt/TarDAL
[25] Han XU. Roadscene database. https://github.com/hanna-xu/RoadScene