{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T07:40:27Z","timestamp":1763106027888,"version":"3.37.3"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T00:00:00Z","timestamp":1719360000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T00:00:00Z","timestamp":1719360000000},"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":"crossref","award":["61806126","61903256"],"award-info":[{"award-number":["61806126","61903256"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Natural Science Foundation of Shanghai","award":["19ZR1455300"],"award-info":[{"award-number":["19ZR1455300"]}]},{"name":"Science and Technology Development Foundation of the Shanghai Institute of Technology","award":["ZQ2023-15"],"award-info":[{"award-number":["ZQ2023-15"]}]},{"name":"Shanghai Science and Technology Innovation Action Plan","award":["22S31903900"],"award-info":[{"award-number":["22S31903900"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00530-024-01356-2","type":"journal-article","created":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T09:03:00Z","timestamp":1719392580000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Multi-branch feature fusion and refinement network for salient object detection"],"prefix":"10.1007","volume":"30","author":[{"given":"Jinyu","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanjiao","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianqian","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,26]]},"reference":[{"key":"1356_CR1","doi-asserted-by":"crossref","unstructured":"Collier, M., Mustafa, B., Kokiopoulou, E., Jenatton, R., Berent, J.: Correlated input-dependent label noise in large-scale image classification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1551\u20131560 (2021)","DOI":"10.1109\/CVPR46437.2021.00160"},{"key":"1356_CR2","doi-asserted-by":"crossref","unstructured":"Li, B., Li, Y., Eliceiri, K.W.: Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14318\u201314328 (2021)","DOI":"10.1109\/CVPR46437.2021.01409"},{"key":"1356_CR3","doi-asserted-by":"crossref","unstructured":"Wang, T.-C., Mallya, A., Liu, M.-Y.: One-shot free-view neural talking-head synthesis for video conferencing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10039\u201310049 (2021)","DOI":"10.1109\/CVPR46437.2021.00991"},{"key":"1356_CR4","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.neucom.2016.10.073","volume":"257","author":"P Zhang","year":"2017","unstructured":"Zhang, P., Zhuo, T., Huang, W., Chen, K., Kankanhalli, M.: Online object tracking based on cnn with spatial-temporal saliency guided sampling. Neurocomputing 257, 115\u2013127 (2017)","journal-title":"Neurocomputing"},{"key":"1356_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107130","volume":"100","author":"P Zhang","year":"2020","unstructured":"Zhang, P., Liu, W., Wang, D., Lei, Y., Wang, H., Lu, H.: Non-rigid object tracking via deep multi-scale spatial-temporal discriminative saliency maps. Pattern Recognit. 100, 107130 (2020)","journal-title":"Pattern Recognit."},{"key":"1356_CR6","doi-asserted-by":"crossref","unstructured":"Zhang, L., Dai, J., Lu, H., He, Y., Wang, G.: A bi-directional message passing model for salient object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1741\u20131750 (2018)","DOI":"10.1109\/CVPR.2018.00187"},{"key":"1356_CR7","doi-asserted-by":"crossref","unstructured":"Zhang, X., Wang, T., Qi, J., Lu, H., Wang, G.: Progressive attention guided recurrent network for salient object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 714\u2013722 (2018)","DOI":"10.1109\/CVPR.2018.00081"},{"key":"1356_CR8","doi-asserted-by":"crossref","unstructured":"Qin, X., Zhang, Z., Huang, C., Gao, C., Dehghan, M., Jagersand, M.: Basnet: boundary-aware salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7479\u20137489 (2019)","DOI":"10.1109\/CVPR.2019.00766"},{"key":"1356_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2021.104337","volume":"117","author":"J Zhang","year":"2022","unstructured":"Zhang, J., Shi, Y., Zhang, Q., Cui, L., Chen, Y., Yi, Y.: Attention guided contextual feature fusion network for salient object detection. Image Vis. Comput. 117, 104337 (2022)","journal-title":"Image Vis. Comput."},{"key":"1356_CR10","doi-asserted-by":"crossref","unstructured":"Zhao, T., Wu, X.: Pyramid feature attention network for saliency detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3085\u20133094 (2019)","DOI":"10.1109\/CVPR.2019.00320"},{"key":"1356_CR11","doi-asserted-by":"crossref","unstructured":"Wei, J., Wang, S., Huang, Q.: F$$^3$$net: fusion, feedback and focus for salient object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 12321\u201312328 (2020)","DOI":"10.1609\/aaai.v34i07.6916"},{"key":"1356_CR12","doi-asserted-by":"crossref","unstructured":"Zhang, M., Liu, T., Piao, Y., Yao, S., Lu, H.: Auto-msfnet: search multi-scale fusion network for salient object detection. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 667\u2013676 (2021)","DOI":"10.1145\/3474085.3475231"},{"key":"1356_CR13","doi-asserted-by":"crossref","unstructured":"Pang, Y., Zhao, X., Zhang, L., Lu, H.: Multi-scale interactive network for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9413\u20139422 (2020)","DOI":"10.1109\/CVPR42600.2020.00943"},{"issue":"11","key":"1356_CR14","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254\u20131259 (1998)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1356_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, J., Ehinger, K.A., Ding, J., Yang, J.: A prior-based graph for salient object detection. In: 2014 IEEE International Conference on Image Processing (ICIP). IEEE, pp. 1175\u20131178 (2014)","DOI":"10.1109\/ICIP.2014.7025234"},{"issue":"3","key":"1356_CR16","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1109\/TPAMI.2014.2345401","volume":"37","author":"M-M Cheng","year":"2014","unstructured":"Cheng, M.-M., Mitra, N.J., Huang, X., Torr, P.H., Hu, S.-M.: Global contrast based salient region detection. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 569\u2013582 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1356_CR17","doi-asserted-by":"crossref","unstructured":"Yan, Q., Xu, L., Shi, J., Jia, J.: Hierarchical saliency detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1155\u20131162 (2013)","DOI":"10.1109\/CVPR.2013.153"},{"key":"1356_CR18","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: 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp. 733\u2013740 (2012)","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"1356_CR19","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, L., Lu, H., Ruan, X., Yang, M.-H.: Saliency detection via graph-based manifold ranking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3166\u20133173 (2013)","DOI":"10.1109\/CVPR.2013.407"},{"key":"1356_CR20","doi-asserted-by":"crossref","unstructured":"Jiang, H., Wang, J., Yuan, Z., Wu, Y., Zheng, N., Li, S.: Salient object detection: a discriminative regional feature integration approach. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2083\u20132090 (2013)","DOI":"10.1109\/CVPR.2013.271"},{"issue":"7","key":"1356_CR21","doi-asserted-by":"publisher","first-page":"3952","DOI":"10.1109\/TII.2018.2884211","volume":"15","author":"C Hong","year":"2018","unstructured":"Hong, C., Yu, J., Zhang, J., Jin, X., Lee, K.-H.: Multimodal face-pose estimation with multitask manifold deep learning. IEEE Trans. Ind. Inform. 15(7), 3952\u20133961 (2018)","journal-title":"IEEE Trans. Ind. Inform."},{"issue":"12","key":"1356_CR22","doi-asserted-by":"publisher","first-page":"5659","DOI":"10.1109\/TIP.2015.2487860","volume":"24","author":"C Hong","year":"2015","unstructured":"Hong, C., Yu, J., Wan, J., Tao, D., Wang, M.: Multimodal deep autoencoder for human pose recovery. IEEE Trans. Image Process. 24(12), 5659\u20135670 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"1356_CR23","first-page":"4727","volume":"35","author":"K Li","year":"2022","unstructured":"Li, K., Lu, J., Zuo, H., Zhang, G.: Dynamic classifier alignment for unsupervised multi-source domain adaptation. IEEE Trans. Knowl. Data Eng. 35(5), 4727\u20134740 (2022)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"1356_CR24","doi-asserted-by":"crossref","unstructured":"Li, K., Lu, J., Zuo, H., Zhang, G.: Multidomain adaptation with sample and source distillation. IEEE Trans. Cybern. (2023)","DOI":"10.1109\/TCYB.2023.3236008"},{"issue":"2","key":"1356_CR25","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1109\/TPAMI.2019.2932058","volume":"44","author":"J Yu","year":"2019","unstructured":"Yu, J., Tan, M., Zhang, H., Rui, Y., Tao, D.: Hierarchical deep click feature prediction for fine-grained image recognition. IEEE Trans. Pattern Anal. Mach. Intell. 44(2), 563\u2013578 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1356_CR26","doi-asserted-by":"crossref","unstructured":"Hou, Q., Cheng, M.-M., Hu, X., Borji, A., Tu, Z., Torr, P.H.: Deeply supervised salient object detection with short connections. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3203\u20133212 (2017)","DOI":"10.1109\/CVPR.2017.563"},{"key":"1356_CR27","doi-asserted-by":"crossref","unstructured":"Liu, J.-J., Hou, Q., Cheng, M.-M., Feng, J., Jiang, J.: A simple pooling-based design for real-time salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3917\u20133926 (2019)","DOI":"10.1109\/CVPR.2019.00404"},{"key":"1356_CR28","doi-asserted-by":"crossref","unstructured":"Wu, Z., Su, L., Huang, Q.: Cascaded partial decoder for fast and accurate salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3907\u20133916 (2019)","DOI":"10.1109\/CVPR.2019.00403"},{"key":"1356_CR29","doi-asserted-by":"crossref","unstructured":"Wang, W., Shen, J., Cheng, M.-M., Shao, L.: An iterative and cooperative top-down and bottom-up inference network for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5968\u20135977 (2019)","DOI":"10.1109\/CVPR.2019.00612"},{"key":"1356_CR30","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"},{"key":"1356_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2022.104423","volume":"120","author":"J Zhang","year":"2022","unstructured":"Zhang, J., Liang, Q., Guo, Q., Yang, J., Zhang, Q., Shi, Y.: R2net: residual refinement network for salient object detection. Image Vis. Comput. 120, 104423 (2022)","journal-title":"Image Vis. Comput."},{"key":"1356_CR32","doi-asserted-by":"crossref","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2881\u20132890 (2017)","DOI":"10.1109\/CVPR.2017.660"},{"key":"1356_CR33","doi-asserted-by":"publisher","first-page":"3125","DOI":"10.1109\/TIP.2022.3164550","volume":"31","author":"Y-H Wu","year":"2022","unstructured":"Wu, Y.-H., Liu, Y., Zhang, L., Cheng, M.-M., Ren, B.: Edn: salient object detection via extremely-downsampled network. IEEE Trans. Image Process. 31, 3125\u20133136 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"1356_CR34","doi-asserted-by":"crossref","unstructured":"Xia, C., Sun, Y., Fang, X., Ge, B., Gao, X., Li, K.-C.: Imsfnet: integrated multi-source feature network for salient object detection. Appl. Intell. 1\u201321 (2023)","DOI":"10.1007\/s10489-023-04636-y"},{"key":"1356_CR35","doi-asserted-by":"crossref","unstructured":"Ding, X., Guo, Y., Ding, G., Han, J.: Acnet: strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1911\u20131920 (2019)","DOI":"10.1109\/ICCV.2019.00200"},{"key":"1356_CR36","unstructured":"Yu, F., Koltun, V.: Multi-scale context aggregation by dilated convolutions. arXiv:1511.07122 (2015)"},{"key":"1356_CR37","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1356_CR38","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1356_CR39","doi-asserted-by":"crossref","unstructured":"Liu, J.-J., Hou, Q., Liu, Z.-A., Cheng, M.-M.: Poolnet+: exploring the potential of pooling for salient object detection. IEEE (2022)","DOI":"10.1109\/TPAMI.2021.3140168"},{"key":"1356_CR40","doi-asserted-by":"crossref","unstructured":"Yu, J., Jiang, Y., Wang, Z., Cao, Z., Huang, T.: Unitbox: an advanced object detection network. In: Proceedings of the 24th ACM International Conference on Multimedia, pp. 516\u2013520 (2016)","DOI":"10.1145\/2964284.2967274"},{"key":"1356_CR41","doi-asserted-by":"crossref","unstructured":"Bokhovkin, A., Burnaev, E.: Boundary loss for remote sensing imagery semantic segmentation. In: International Symposium on Neural Networks. Springer, pp. 388\u2013401 (2019)","DOI":"10.1007\/978-3-030-22808-8_38"},{"key":"1356_CR42","doi-asserted-by":"crossref","unstructured":"Yan, Q., Xu, L., Shi, J., Jia, J.: Hierarchical saliency detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1155\u20131162 (2013)","DOI":"10.1109\/CVPR.2013.153"},{"key":"1356_CR43","doi-asserted-by":"crossref","unstructured":"Li, G., Yu, Y.: Visual saliency based on multiscale deep features. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5455\u20135463 (2015)","DOI":"10.1109\/CVPR.2015.7299184"},{"key":"1356_CR44","doi-asserted-by":"crossref","unstructured":"Li, Y., Hou, X., Koch, C., Rehg, J.M., Yuille, A.L.: The secrets of salient object segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 280\u2013287 (2014)","DOI":"10.1109\/CVPR.2014.43"},{"key":"1356_CR45","doi-asserted-by":"crossref","unstructured":"Yang, C., Zhang, L., Lu, H., Ruan, X., Yang, M.-H.: Saliency detection via graph-based manifold ranking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3166\u20133173 (2013)","DOI":"10.1109\/CVPR.2013.407"},{"key":"1356_CR46","doi-asserted-by":"crossref","unstructured":"Wang, L., Lu, H., Wang, Y., Feng, M., Wang, D., Yin, B., Ruan, X.: Learning to detect salient objects with image-level supervision. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 136\u2013145 (2017)","DOI":"10.1109\/CVPR.2017.404"},{"key":"1356_CR47","doi-asserted-by":"crossref","unstructured":"Fan, D.-P., Cheng, M.-M., Liu, J.-J., Gao, S.-H., Hou, Q., Borji, A.: Salient objects in clutter: bringing salient object detection to the foreground. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 186\u2013202 (2018)","DOI":"10.1007\/978-3-030-01267-0_12"},{"key":"1356_CR48","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: 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp. 733\u2013740 (2012)","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"1356_CR49","doi-asserted-by":"crossref","unstructured":"Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp. 1597\u20131604 (2009)","DOI":"10.1109\/CVPRW.2009.5206596"},{"key":"1356_CR50","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":"1356_CR51","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:1805.10421 (2018)","DOI":"10.24963\/ijcai.2018\/97"},{"key":"1356_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107146","volume":"100","author":"R Soleymani","year":"2020","unstructured":"Soleymani, R., Granger, E., Fumera, G.: F-measure curves: a tool to visualize classifier performance under imbalance. Pattern Recognit. 100, 107146 (2020)","journal-title":"Pattern Recognit."},{"key":"1356_CR53","doi-asserted-by":"publisher","first-page":"8652","DOI":"10.1109\/TIP.2020.3017352","volume":"29","author":"J-J Liu","year":"2020","unstructured":"Liu, J.-J., Hou, Q., Cheng, M.-M.: Dynamic feature integration for simultaneous detection of salient object, edge, and skeleton. IEEE Trans. Image Process. 29, 8652\u20138667 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"1356_CR54","doi-asserted-by":"crossref","unstructured":"Feng, M., Lu, H., Ding, E.: Attentive feedback network for boundary-aware salient object detection. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)","DOI":"10.1109\/CVPR.2019.00172"},{"key":"1356_CR55","doi-asserted-by":"crossref","unstructured":"Deng, Z., Hu, X., Zhu, L., Xu, X., Qin, J., Han, G., Heng, P.-A.: R3net: recurrent residual refinement network for saliency detection. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. AAAI Press, Menlo Park, pp. 684\u2013690 (2018)","DOI":"10.24963\/ijcai.2018\/95"},{"key":"1356_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":"1356_CR57","doi-asserted-by":"crossref","unstructured":"Pang, Y., Zhao, X., Zhang, L., Lu, H.: Multi-scale interactive network for salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9413\u20139422 (2020)","DOI":"10.1109\/CVPR42600.2020.00943"},{"key":"1356_CR58","doi-asserted-by":"crossref","unstructured":"Ma, M., Xia, C., Li, J.: Pyramidal feature shrinking for salient object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 2311\u20132318 (2021)","DOI":"10.1609\/aaai.v35i3.16331"},{"key":"1356_CR59","doi-asserted-by":"crossref","unstructured":"Chen, Z., Xu, Q., Cong, R., Huang, Q.: Global context-aware progressive aggregation network for salient object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 10599\u201310606 (2020)","DOI":"10.1609\/aaai.v34i07.6633"},{"key":"1356_CR60","doi-asserted-by":"crossref","unstructured":"Lee, M.S., Shin, W., Han, S.W.: Tracer: extreme attention guided salient object tracing network. arXiv:2112.07380 (2021)","DOI":"10.1609\/aaai.v36i11.21633"},{"key":"1356_CR61","doi-asserted-by":"crossref","unstructured":"Yu, S., Zhang, B., Xiao, J., Lim, E.G.: Structure-consistent weakly supervised salient object detection with local saliency coherence. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, pp. 3234\u20133242 (2021)","DOI":"10.1609\/aaai.v35i4.16434"},{"key":"1356_CR62","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition. Ieee, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"1356_CR63","doi-asserted-by":"crossref","unstructured":"Wu, Z., Su, L., Huang, Q.: Cascaded partial decoder for fast and accurate salient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3907\u20133916 (2019)","DOI":"10.1109\/CVPR.2019.00403"},{"key":"1356_CR64","doi-asserted-by":"crossref","unstructured":"Wu, Z., Su, L., Huang, Q.: Stacked cross refinement network for edge-aware salient object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7264\u20137273 (2019)","DOI":"10.1109\/ICCV.2019.00736"},{"key":"1356_CR65","doi-asserted-by":"crossref","unstructured":"Zhao, X., Pang, Y., Zhang, L., Lu, H., Zhang, L.: Suppress and balance: a simple gated network for salient object detection. In: European Conference on Computer Vision. Springer, pp. 35\u201351 (2020)","DOI":"10.1007\/978-3-030-58536-5_3"},{"key":"1356_CR66","doi-asserted-by":"crossref","unstructured":"Zhou, H., Xie, X., Lai, J.-H., Chen, Z., Yang, L.: Interactive two-stream decoder for accurate and fast saliency detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9141\u20139150 (2020)","DOI":"10.1109\/CVPR42600.2020.00916"},{"key":"1356_CR67","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Xia, C., Xie, C., Li, J.: Complementary trilateral decoder for fast and accurate salient object detection. In: Proceedings of the 29th Acm International Conference on Multimedia, pp. 4967\u20134975 (2021)","DOI":"10.1145\/3474085.3475494"},{"key":"1356_CR68","doi-asserted-by":"publisher","first-page":"6855","DOI":"10.1109\/TIP.2021.3099405","volume":"30","author":"J Li","year":"2021","unstructured":"Li, J., Su, J., Xia, C., Ma, M., Tian, Y.: Salient object detection with purificatory mechanism and structural similarity loss. IEEE Trans. Image Process. 30, 6855\u20136868 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"1356_CR69","doi-asserted-by":"crossref","unstructured":"Zhuge, M., Fan, D.-P., Liu, N., Zhang, D., Xu, D., Shao, L.: Salient object detection via integrity learning. IEEE Trans. Pattern Anal. Mach. Intell. (2022)","DOI":"10.1109\/TPAMI.2022.3179526"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01356-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-024-01356-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01356-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T18:56:35Z","timestamp":1732301795000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-024-01356-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,26]]},"references-count":69,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["1356"],"URL":"https:\/\/doi.org\/10.1007\/s00530-024-01356-2","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"type":"print","value":"0942-4962"},{"type":"electronic","value":"1432-1882"}],"subject":[],"published":{"date-parts":[[2024,6,26]]},"assertion":[{"value":"18 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 May 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2024","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 manuscript is approved by all co-authors and there are no Conflict of interest to report.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"190"}}