{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T16:56:23Z","timestamp":1772643383503,"version":"3.50.1"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52571332"],"award-info":[{"award-number":["52571332"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s00371-026-04359-4","type":"journal-article","created":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T16:42:48Z","timestamp":1769359368000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A dual-branch RGB-T salient object detection via spatial-frequency integration"],"prefix":"10.1007","volume":"42","author":[{"given":"Xiaosheng","family":"Yu","sequence":"first","affiliation":[]},{"given":"Jiawei","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jubo","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,25]]},"reference":[{"key":"4359_CR1","doi-asserted-by":"publisher","first-page":"1052","DOI":"10.1109\/TIP.2023.3238648","volume":"32","author":"R Xu","year":"2023","unstructured":"Xu, R., Wang, C., Zhang, J., Xu, S., Meng, W., Zhang, X.: Rssformer: foreground saliency enhancement for remote sensing land-cover segmentation. IEEE Trans. Image Process. 32, 1052\u20131064 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"4359_CR2","first-page":"185","volume":"19","author":"C Guo","year":"2009","unstructured":"Guo, C., Zhang, L.: A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Trans. Image Process. 19(1), 185\u2013198 (2009)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR3","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.patcog.2019.05.002","volume":"94","author":"CF Flores","year":"2019","unstructured":"Flores, C.F., Gonzalez-Garcia, A., van de Weijer, J., Raducanu, B.: Saliency for fine-grained object recognition in domains with scarce training data. Pattern Recogn. 94, 62\u201373 (2019)","journal-title":"Pattern Recogn."},{"issue":"1","key":"4359_CR4","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s00371-024-03312-7","volume":"41","author":"MA Eldosoky","year":"2025","unstructured":"Eldosoky, M.A., Li, J.P., Haq, A.U., Zeng, F., Xu, M., Khan, S., Khan, I.: Wallnet: hierarchical visual attention-based model for putty bulge terminal points detection. Vis. Comput. 41(1), 99\u2013114 (2025)","journal-title":"Vis. Comput."},{"key":"4359_CR5","doi-asserted-by":"crossref","unstructured":"Piao, Z., Feng, F., Dang, R., Wang, W., Zhou, S., Han, Y.: Enhancing few-shot object detection through mixing and separating tuning strategies: Z. Piao et al. In: The Visual Computer, pp. 1\u201318 (2025)","DOI":"10.1007\/s00371-025-04043-z"},{"key":"4359_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120286","volume":"662","author":"Y Zhou","year":"2024","unstructured":"Zhou, Y., Xia, H., Yu, D., Cheng, J., Li, J.: Outlier detection method based on high-density iteration. Inf. Sci. 662, 120286 (2024)","journal-title":"Inf. Sci."},{"issue":"12","key":"4359_CR7","doi-asserted-by":"publisher","first-page":"8940","DOI":"10.1109\/TGRS.2020.2992301","volume":"58","author":"C Fu","year":"2020","unstructured":"Fu, C., Xu, J., Lin, F., Guo, F., Liu, T., Zhang, Z.: Object saliency-aware dual regularized correlation filter for real-time aerial tracking. IEEE Trans. Geosci. Remote Sens. 58(12), 8940\u20138951 (2020)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"4359_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2025.111486","volume":"164","author":"DC Bui","year":"2025","unstructured":"Bui, D.C., Le, T.V., Ngo, B.H., Choi, T.J.: Clear: cross-transformers with pre-trained language model for person attribute recognition and retrieval. Pattern Recogn. 164, 111486 (2025)","journal-title":"Pattern Recogn."},{"key":"4359_CR9","doi-asserted-by":"crossref","unstructured":"Bui, D.C., Le, T.V., Ngo, B.H.: C2t-net: channel-aware cross-fused transformer-style networks for pedestrian attribute recognition. In: IEEE\/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), vol. 2024, pp. 351\u2013358 (2024)","DOI":"10.1109\/WACVW60836.2024.00043"},{"key":"4359_CR10","doi-asserted-by":"crossref","unstructured":"Wang, J., Lu, X., Bennamoun, M., Sheng, B.: Non-rigid point cloud registration via anisotropic hybrid field harmonization. IEEE Trans. Pattern Anal. Mach. Intell. (2025)","DOI":"10.1109\/TPAMI.2025.3572584"},{"issue":"1","key":"4359_CR11","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2201","volume":"35","author":"X Zhu","year":"2024","unstructured":"Zhu, X., Yao, X., Zhang, J., Zhu, M., You, L., Yang, X., Zhang, J., Zhao, H., Zeng, D.: Tmsdnet: transformer with multi-scale dense network for single and multi-view 3d reconstruction. Comput. Anim. Virt. Worlds 35(1), e2201 (2024)","journal-title":"Comput. Anim. Virt. Worlds"},{"issue":"3","key":"4359_CR12","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2275","volume":"35","author":"S Feng","year":"2024","unstructured":"Feng, S., Hou, F., Chen, J., Wang, W.: Extracting roads from satellite images via enhancing road feature investigation in learning. Comput. Anim. Virt. Worlds 35(3), e2275 (2024)","journal-title":"Comput. Anim. Virt. Worlds"},{"issue":"21","key":"4359_CR13","doi-asserted-by":"publisher","first-page":"2245","DOI":"10.1016\/j.scib.2022.10.006","volume":"67","author":"S He","year":"2022","unstructured":"He, S., Ding, L., Xiong, Z., Spicer, R.A., Farnsworth, A., Valdes, P.J., Wang, C., Cai, F., Wang, H., Sun, Y., et al.: A distinctive eocene asian monsoon and modern biodiversity resulted from the rise of eastern tibet. Sci. Bull. 67(21), 2245\u20132258 (2022)","journal-title":"Sci. Bull."},{"key":"4359_CR14","doi-asserted-by":"crossref","unstructured":"Wang, W., Shen, J., Dong, X., Borji, A.: Salient object detection driven by fixation prediction. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1711\u20131720 (2018)","DOI":"10.1109\/CVPR.2018.00184"},{"key":"4359_CR15","first-page":"1","volume":"70","author":"AK Gupta","year":"2021","unstructured":"Gupta, A.K., Seal, A., Khanna, P., Herrera-Viedma, E., Krejcar, O.: Almnet: adjacent layer driven multiscale features for salient object detection. IEEE Trans. Instrum. Meas. 70, 1\u201314 (2021)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"4359_CR16","first-page":"1","volume":"72","author":"B Wan","year":"2023","unstructured":"Wan, B., Zhou, X., Zheng, B., Yin, H., Zhu, Z., Wang, H., Sun, Y., Zhang, J., Yan, C.: Lfrnet: localizing, focus, and refinement network for salient object detection of surface defects. IEEE Trans. Instrum. Meas. 72, 1\u201312 (2023)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"4359_CR17","doi-asserted-by":"crossref","unstructured":"Wang, G., Li, C., Ma, Y., Zheng, A., Tang, J., Luo, B.: Rgb-t saliency detection benchmark: dataset, baselines, analysis and a novel approach. In: Chinese Conference on Image and Graphics Technologies, pp. 359\u2013369. Springer (2018)","DOI":"10.1007\/978-981-13-1702-6_36"},{"key":"4359_CR18","doi-asserted-by":"crossref","unstructured":"Shigematsu, R., Feng, D., You, S., Barnes, N.: Learning rgb-d salient object detection using background enclosure, depth contrast, and top-down features. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp. 2749\u20132757 (2017)","DOI":"10.1109\/ICCVW.2017.323"},{"key":"4359_CR19","doi-asserted-by":"publisher","first-page":"7790","DOI":"10.1109\/TIP.2021.3109518","volume":"30","author":"W Zhou","year":"2021","unstructured":"Zhou, W., Liu, J., Lei, J., Yu, L., Hwang, J.-N.: Gmnet: graded-feature multilabel-learning network for rgb-thermal urban scene semantic segmentation. IEEE Trans. Image Process. 30, 7790\u20137802 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR20","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol.\u00a030 (2017)"},{"issue":"1","key":"4359_CR21","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.vrih.2022.07.006","volume":"5","author":"M Zhang","year":"2023","unstructured":"Zhang, M., Tian, X.: Transformer architecture based on mutual attention for image-anomaly detection. Virtual Reality Intell. Hardware 5(1), 57\u201367 (2023)","journal-title":"Virtual Reality Intell. Hardware"},{"key":"4359_CR22","doi-asserted-by":"crossref","unstructured":"Ranftl, R., Bochkovskiy, A., Koltun, V.: Vision transformers for dense prediction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12179\u201312188 (2021)","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"4359_CR23","doi-asserted-by":"crossref","unstructured":"Wen, Y., Luo, B., Shi, W., Ji, J., Cao, W., Yang, X., Sheng, B.: Sat-net: structure-aware transformer-based attention fusion network for low-quality retinal fundus images enhancement. IEEE Trans. Multimed. (2025)","DOI":"10.1109\/TMM.2025.3565935"},{"key":"4359_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, P., Zhao, J., Wang, D., Lu, H., Ruan, X.: Visible-thermal uav tracking: a large-scale benchmark and new baseline. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8886\u20138895 (2022)","DOI":"10.1109\/CVPR52688.2022.00868"},{"issue":"7","key":"4359_CR25","doi-asserted-by":"publisher","first-page":"4486","DOI":"10.1109\/TCSVT.2021.3127149","volume":"32","author":"Z Liu","year":"2021","unstructured":"Liu, Z., Tan, Y., He, Q., Xiao, Y.: Swinnet: swin transformer drives edge-aware rgb-d and rgb-t salient object detection. IEEE Trans. Circuits Syst. Video Technol. 32(7), 4486\u20134497 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"2","key":"4359_CR26","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1109\/TCSVT.2022.3202563","volume":"33","author":"B Tang","year":"2022","unstructured":"Tang, B., Liu, Z., Tan, Y., He, Q.: Hrtransnet: Hrformer-driven two-modality salient object detection. IEEE Trans. Circuits Syst. Video Technol. 33(2), 728\u2013742 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4359_CR27","doi-asserted-by":"publisher","first-page":"3027","DOI":"10.1109\/TIP.2023.3275538","volume":"32","author":"W Zhou","year":"2023","unstructured":"Zhou, W., Sun, F., Jiang, Q., Cong, R., Hwang, J.-N.: Wavenet: wavelet network with knowledge distillation for rgb-t salient object detection. IEEE Trans. Image Process. 32, 3027\u20133039 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR28","doi-asserted-by":"crossref","unstructured":"Tu, Z., Xia, T., Li, C., Lu, Y., Tang, J.: M3s-nir: multi-modal multi-scale noise-insensitive ranking for rgb-t saliency detection. In: 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), pp. 141\u2013146. IEEE (2019)","DOI":"10.1109\/MIPR.2019.00032"},{"issue":"3","key":"4359_CR29","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.1109\/TCSVT.2021.3077058","volume":"32","author":"W Zhou","year":"2021","unstructured":"Zhou, W., Guo, Q., Lei, J., Yu, L., Hwang, J.-N.: Ecffnet: effective and consistent feature fusion network for rgb-t salient object detection. IEEE Trans. Circuits Syst. Video Technol. 32(3), 1224\u20131235 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4359_CR30","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1109\/TIP.2023.3242775","volume":"32","author":"W Zhou","year":"2023","unstructured":"Zhou, W., Zhu, Y., Lei, J., Yang, R., Yu, L.: Lsnet: lightweight spatial boosting network for detecting salient objects in rgb-thermal images. IEEE Trans. Image Process. 32, 1329\u20131340 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2024.105302","volume":"152","author":"Q Xu","year":"2024","unstructured":"Xu, Q., Di, Z., Dong, H., Yang, G.: Feature differences reduction and specific features preserving network for rgb-t salient object detection. Image Vis. Comput. 152, 105302 (2024)","journal-title":"Image Vis. Comput."},{"key":"4359_CR32","doi-asserted-by":"crossref","unstructured":"Tang, H., Li, Z., Zhang, D., He, S., Tang, J.: Divide-and-conquer: confluent triple-flow network for rgb-t salient object detection. IEEE Trans. Pattern Anal. Mach. Intell. (2024)","DOI":"10.1109\/TPAMI.2024.3511621"},{"key":"4359_CR33","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhu, Y., Adam, H., Yuille, A., Chen, L.-C.: Max-deeplab: end-to-end panoptic segmentation with mask transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5463\u20135474 (2021)","DOI":"10.1109\/CVPR46437.2021.00542"},{"key":"4359_CR34","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.neucom.2022.04.062","volume":"493","author":"K Zeng","year":"2022","unstructured":"Zeng, K., Ma, Q., Wu, J., Xiang, S., Shen, T., Zhang, L.: Nlfftnet: a non-local feature fusion transformer network for multi-scale object detection. Neurocomputing 493, 15\u201327 (2022)","journal-title":"Neurocomputing"},{"key":"4359_CR35","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1016\/j.ins.2022.06.091","volume":"608","author":"Z He","year":"2022","unstructured":"He, Z., Lin, M., Xu, Z., Yao, Z., Chen, H., Alhudhaif, A., Alenezi, F.: Deconv-transformer (dect): a histopathological image classification model for breast cancer based on color deconvolution and transformer architecture. Inf. Sci. 608, 1093\u20131112 (2022)","journal-title":"Inf. Sci."},{"key":"4359_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128149","volume":"600","author":"J Luo","year":"2024","unstructured":"Luo, J., Li, Y., Li, B., Zhang, X., Li, C., Chenjin, Z., He, J., Liang, Y.: Transformer-based cross-modality interaction guidance network for rgb-t salient object detection. Neurocomputing 600, 128149 (2024)","journal-title":"Neurocomputing"},{"key":"4359_CR37","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.1109\/TIP.2023.3270801","volume":"32","author":"H Zhou","year":"2023","unstructured":"Zhou, H., Tian, C., Zhang, Z., Li, C., Ding, Y., Xie, Y., Li, Z.: Position-aware relation learning for rgb-thermal salient object detection. IEEE Trans. Image Process. 32, 2593\u20132607 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR38","doi-asserted-by":"publisher","first-page":"892","DOI":"10.1109\/TIP.2023.3234702","volume":"32","author":"Y Pang","year":"2023","unstructured":"Pang, Y., Zhao, X., Zhang, L., Lu, H.: Caver: cross-modal view-mixed transformer for bi-modal salient object detection. IEEE Trans. Image Process. 32, 892\u2013904 (2023)","journal-title":"IEEE Trans. Image Process."},{"key":"4359_CR39","doi-asserted-by":"crossref","unstructured":"Wang, A., Islam, M., Xu, M., Ren, H.: Curriculum-based augmented Fourier domain adaptation for robust medical image segmentation. IEEE Trans. Automat. Sci. Eng. (2023)","DOI":"10.1109\/TASE.2023.3295600"},{"key":"4359_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2025.130376","volume":"641","author":"X Zhang","year":"2025","unstructured":"Zhang, X., Xu, C., Fan, G., Hua, Z., Li, J., Zhou, J.: Fscmf: a dual-branch frequency-spatial joint perception cross-modality network for visible and infrared image fusion. Neurocomputing 641, 130376 (2025)","journal-title":"Neurocomputing"},{"key":"4359_CR41","doi-asserted-by":"crossref","unstructured":"Kong, L., Dong, J., Ge, J., Li, M., Pan, J.: Efficient frequency domain-based transformers for high-quality image deblurring. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5886\u20135895 (2023)","DOI":"10.1109\/CVPR52729.2023.00570"},{"key":"4359_CR42","doi-asserted-by":"crossref","unstructured":"Chu, T., Chen, J., Sun, J., Lian, S., Wang, Z., Zuo, Z., Zhao, L., Xing, W., Lu, D.: Rethinking fast fourier convolution in image inpainting. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 23195\u201323205 (2023)","DOI":"10.1109\/ICCV51070.2023.02120"},{"key":"4359_CR43","doi-asserted-by":"crossref","unstructured":"Yang, Y., Yuan, G., Li, J.: Sffnet: a wavelet-based spatial and frequency domain fusion network for remote sensing segmentation. IEEE Trans. Geosci. Remote Sens. (2024)","DOI":"10.1109\/TGRS.2024.3427370"},{"key":"4359_CR44","doi-asserted-by":"publisher","first-page":"8813","DOI":"10.1109\/JSTARS.2025.3551093","volume":"18","author":"X Zhang","year":"2025","unstructured":"Zhang, X., Dong, K., Cheng, D., Hua, Z., Li, J.: Stwanet: spatio-temporal wavelet attention aggregation network for remote sensing change detection. IEEE J. Select. Top. Appl. Earth Observ. Remote Sens. 18, 8813\u20138830 (2025)","journal-title":"IEEE J. Select. Top. Appl. Earth Observ. Remote Sens."},{"issue":"1","key":"4359_CR45","first-page":"81","volume":"4","author":"AB Watson","year":"1994","unstructured":"Watson, A.B., et al.: Image compression using the discrete cosine transform. Math. J. 4(1), 81 (1994)","journal-title":"Math. J."},{"key":"4359_CR46","doi-asserted-by":"crossref","unstructured":"Tatsunami, Y., Taki, M.: Fft-based dynamic token mixer for vision. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a038, no.\u00a014, pp. 15328\u201315336 (2024)","DOI":"10.1609\/aaai.v38i14.29457"},{"key":"4359_CR47","doi-asserted-by":"crossref","unstructured":"Duan, W., Ji, L., Chen, S., Zhu, S., Ye, M.: Triple-domain feature learning with frequency-aware memory enhancement for moving infrared small target detection. IEEE Trans. Geosci. Remote Sens. (2024)","DOI":"10.1109\/TGRS.2024.3452175"},{"key":"4359_CR48","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1016\/j.neucom.2022.04.015","volume":"491","author":"X Jin","year":"2022","unstructured":"Jin, X., Guo, C., He, Z., Xu, J., Wang, Y., Su, Y.: Fcmnet: frequency-aware cross-modality attention networks for rgb-d salient object detection. Neurocomputing 491, 414\u2013425 (2022)","journal-title":"Neurocomputing"},{"key":"4359_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.110043","volume":"146","author":"H Zhou","year":"2024","unstructured":"Zhou, H., Tian, C., Zhang, Z., Li, C., Xie, Y., Li, Z.: Frequency-aware feature aggregation network with dual-task consistency for rgb-t salient object detection. Pattern Recogn. 146, 110043 (2024)","journal-title":"Pattern Recogn."},{"key":"4359_CR50","doi-asserted-by":"crossref","unstructured":"Wei, J., Wang, S., Wu, Z., Su, C., Huang, Q., Tian, Q.: Label decoupling framework for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13025\u201313034 (2020)","DOI":"10.1109\/CVPR42600.2020.01304"},{"issue":"1","key":"4359_CR51","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10479-005-5724-z","volume":"134","author":"P-T De Boer","year":"2005","unstructured":"De Boer, P.-T., Kroese, D.P., Mannor, S., Rubinstein, R.Y.: A tutorial on the cross-entropy method. Ann. Oper. Res. 134(1), 19\u201367 (2005)","journal-title":"Ann. Oper. Res."},{"key":"4359_CR52","doi-asserted-by":"crossref","unstructured":"M\u00e1ttyus, G., Luo, W., Urtasun, R.: Deeproadmapper: extracting road topology from aerial images. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3438\u20133446 (2017)","DOI":"10.1109\/ICCV.2017.372"},{"issue":"1","key":"4359_CR53","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1109\/TMM.2019.2924578","volume":"22","author":"Z Tu","year":"2019","unstructured":"Tu, Z., Xia, T., Li, C., Wang, X., Ma, Y., Tang, J.: Rgb-t image saliency detection via collaborative graph learning. IEEE Trans. Multimed. 22(1), 160\u2013173 (2019)","journal-title":"IEEE Trans. Multimed."},{"key":"4359_CR54","doi-asserted-by":"publisher","first-page":"4163","DOI":"10.1109\/TMM.2022.3171688","volume":"25","author":"Z Tu","year":"2022","unstructured":"Tu, Z., Ma, Y., Li, Z., Li, C., Xu, J., Liu, Y.: Rgbt salient object detection: a large-scale dataset and benchmark. IEEE Trans. Multimed. 25, 4163\u20134176 (2022)","journal-title":"IEEE Trans. Multimed."},{"key":"4359_CR55","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Gong, C., Cao, Y., Ren, B., Cheng, M.-M., Borji, A.: Enhanced-alignment measure for binary foreground map evaluation. arXiv preprint arXiv:1805.10421 (2018)","DOI":"10.24963\/ijcai.2018\/97"},{"key":"4359_CR56","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., Borji, A.: Structure-measure: a new way to evaluate foreground maps. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4548\u20134557 (2017)","DOI":"10.1109\/ICCV.2017.487"},{"key":"4359_CR57","doi-asserted-by":"crossref","unstructured":"Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2009, pp. 1597\u20131604. IEEE (2009)","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"4359_CR58","doi-asserted-by":"crossref","unstructured":"Margolin, R., Zelnik-Manor, L., Tal, A.: How to evaluate foreground maps? In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2014)","DOI":"10.1109\/CVPR.2014.39"},{"key":"4359_CR59","doi-asserted-by":"crossref","unstructured":"Perazzi, F., Kr\u00e4henb\u00fchl, P., Pritch, Y., Hornung, A.: Saliency filters: contrast based filtering for salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2012, pp. 733\u2013740. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"4359_CR60","first-page":"18261","volume":"33","author":"Y Liu","year":"2020","unstructured":"Liu, Y., Gao, Y., Yin, W.: An improved analysis of stochastic gradient descent with momentum. Adv. Neural Inf. Process. Syst. 33, 18261\u201318271 (2020)","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"8","key":"4359_CR61","doi-asserted-by":"publisher","first-page":"7344","DOI":"10.1109\/TCSVT.2024.3375505","volume":"34","author":"K Wang","year":"2024","unstructured":"Wang, K., Tu, Z., Li, C., Zhang, C., Luo, B.: Learning adaptive fusion bank for multi-modal salient object detection. IEEE Trans. Circuits Syst. Video Technol. 34(8), 7344\u20137358 (2024)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4359_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112126","volume":"299","author":"M Zhong","year":"2024","unstructured":"Zhong, M., Sun, J., Ren, P., Wang, F., Sun, F.: Magnet: multi-scale awareness and global fusion network for rgb-d salient object detection. Knowl. Based Syst. 299, 112126 (2024)","journal-title":"Knowl. Based Syst."},{"key":"4359_CR63","doi-asserted-by":"crossref","unstructured":"Gao, H., Wang, F., Wang, M., Sun, F., Li, H.: Highly efficient rgb-d salient object detection with adaptive fusion and attention regulation. IEEE Trans. Circuits Syst. Video Technol. (2024)","DOI":"10.1109\/TCSVT.2024.3502244"},{"key":"4359_CR64","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125278","volume":"259","author":"J Han","year":"2025","unstructured":"Han, J., Wang, M., Wu, W., Jia, X.: Perceptual localization and focus refinement network for rgb-d salient object detection. Expert Syst. Appl. 259, 125278 (2025)","journal-title":"Expert Syst. Appl."},{"key":"4359_CR65","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"4359_CR66","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"4359_CR67","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.113771","volume":"7","author":"BH Ngo","year":"2025","unstructured":"Ngo, B.H., Choi, T.J.: Cross-domain knowledge distillation for domain adaptation with gcn-driven mlp generalization. Appl. Soft Comput. 7, 113771 (2025)","journal-title":"Appl. Soft Comput."},{"key":"4359_CR68","doi-asserted-by":"publisher","first-page":"166488","DOI":"10.1109\/ACCESS.2021.3136567","volume":"9","author":"BH Ngo","year":"2021","unstructured":"Ngo, B.H., Kim, J.H., Chae, Y.J., Cho, S.I.: Multi-view collaborative learning for semi-supervised domain adaptation. IEEE Access 9, 166488\u2013166501 (2021)","journal-title":"IEEE Access"},{"key":"4359_CR69","doi-asserted-by":"publisher","first-page":"36267","DOI":"10.1109\/ACCESS.2024.3374105","volume":"12","author":"BH Ngo","year":"2024","unstructured":"Ngo, B.H., Lam, B.T., Nguyen, T.H., Dinh, Q.V., Choi, T.J.: Dual dynamic consistency regularization for semi-supervised domain adaptation. IEEE Access 12, 36267\u201336279 (2024)","journal-title":"IEEE Access"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04359-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-026-04359-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04359-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T12:45:23Z","timestamp":1772628323000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-026-04359-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":69,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["4359"],"URL":"https:\/\/doi.org\/10.1007\/s00371-026-04359-4","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"15 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"141"}}