{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T18:06:00Z","timestamp":1784657160839,"version":"3.55.0"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"AnHui Province Key Laboratory of Infrared and Low-Temperature Plasma","award":["NO.IRKL2022KF07"],"award-info":[{"award-number":["NO.IRKL2022KF07"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1007\/s00371-022-02611-1","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:02:51Z","timestamp":1658142171000},"page":"4593-4607","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":85,"title":["TPRNet: camouflaged object detection via transformer-induced progressive refinement network"],"prefix":"10.1007","volume":"39","author":[{"given":"Qiao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanliang","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2442-330X","authenticated-orcid":false,"given":"Hongbo","family":"Bi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,7,18]]},"reference":[{"key":"2611_CR1","doi-asserted-by":"crossref","unstructured":"Amit, S.N.K.B., Shiraishi, S., Inoshita, T., Aoki, Y.: Analysis of satellite images for disaster detection. In: 2016 IEEE International geoscience and remote sensing symposium (IGARSS), pp. 5189\u20135192. IEEE (2016)","DOI":"10.1109\/IGARSS.2016.7730352"},{"key":"2611_CR2","unstructured":"Ba, J.L., Kiros, J.R., Hinton, G.E.: Layer normalization. arXiv preprint arXiv:1607.06450 (2016)"},{"issue":"5","key":"2611_CR3","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1007\/s00371-020-01842-4","volume":"37","author":"H Bi","year":"2021","unstructured":"Bi, H., Wang, K., Lu, D., Wu, C., Wang, W., Yang, L.: C 2 net: a complementary co-saliency detection network. Vis. Comput. 37(5), 911\u2013923 (2021)","journal-title":"Vis. Comput."},{"key":"2611_CR4","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3124952","author":"H Bi","year":"2021","unstructured":"Bi, H., Zhang, C., Wang, K., Tong, J., Zheng, F.: Rethinking camouflaged object detection: models and datasets. IEEE Trans. Circuits Syst. Video Technol. (2021). https:\/\/doi.org\/10.1109\/TCSVT.2021.3124952","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"2611_CR5","doi-asserted-by":"crossref","unstructured":"Cui, Y., Cao, Z., Xie, Y., Jiang, X., Tao, F., Chen, Y.V., Li, L., Liu, D.: Dg-labeler and dgl-mots dataset: Boost the autonomous driving perception. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 58\u201367 (2022)","DOI":"10.1109\/WACV51458.2022.00347"},{"key":"2611_CR6","doi-asserted-by":"crossref","unstructured":"Cui, Y., Yan, L., Cao, Z., Liu, D.: Tf-blender: Temporal feature blender for video object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8138\u20138147 (2021)","DOI":"10.1109\/ICCV48922.2021.00803"},{"key":"2611_CR7","unstructured":"Dong, B., Zhuge, M., Wang, Y., Bi, H., Chen, G.: Towards accurate camouflaged object detection with mixture convolution and interactive fusion. arXiv preprint arXiv:2101.056871(2) (2021)"},{"key":"2611_CR8","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al.: An image is worth 16x16 words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"2611_CR9","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":"2611_CR10","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":"2611_CR11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3085766","author":"DP Fan","year":"2021","unstructured":"Fan, D.P., Ji, G.P., Cheng, M.M., Shao, L.: Concealed object detection. IEEE Trans. Pattern Anal. Mach. Intell. (2021). https:\/\/doi.org\/10.1109\/TPAMI.2021.3085766","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2611_CR12","doi-asserted-by":"crossref","unstructured":"Fan, D.P., Ji, G.P., Sun, G., Cheng, M.M., Shen, J., Shao, L.: Camouflaged object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 2777\u20132787 (2020)","DOI":"10.1109\/CVPR42600.2020.00285"},{"key":"2611_CR13","doi-asserted-by":"crossref","unstructured":"Fan, D.P., Ji, G.P., Zhou, T., Chen, G., Fu, H., Shen, J., Shao, L.: Pranet: Parallel reverse attention network for polyp segmentation. In: International conference on medical image computing and computer-assisted intervention, pp. 263\u2013273. Springer (2020)","DOI":"10.1007\/978-3-030-59725-2_26"},{"issue":"8","key":"2611_CR14","doi-asserted-by":"publisher","first-page":"2626","DOI":"10.1109\/TMI.2020.2996645","volume":"39","author":"DP Fan","year":"2020","unstructured":"Fan, D.P., Zhou, T., Ji, G.P., Zhou, Y., Chen, G., Fu, H., Shen, J., Shao, L.: Inf-net: automatic covid-19 lung infection segmentation from ct images. IEEE Trans. Med. Imaging 39(8), 2626\u20132637 (2020)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"2611_CR15","doi-asserted-by":"crossref","unstructured":"Fu, J., Liu, J., Tian, H., Li, Y., Bao, Y., Fang, Z., Lu, H.: Dual attention network for scene segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp. 3146\u20133154 (2019)","DOI":"10.1109\/CVPR.2019.00326"},{"issue":"2","key":"2611_CR16","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TPAMI.2019.2938758","volume":"43","author":"SH Gao","year":"2019","unstructured":"Gao, S.H., Cheng, M.M., Zhao, K., Zhang, X.Y., Yang, M.H., Torr, P.: Res2net: a new multi-scale backbone architecture. IEEE Trans. Pattern Anal. Mach. Intell. 43(2), 652\u2013662 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2611_CR17","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":"2611_CR18","doi-asserted-by":"publisher","first-page":"2201","DOI":"10.1016\/j.proeng.2011.08.412","volume":"15","author":"JYYHW Hou","year":"2011","unstructured":"Hou, J.Y.Y.H.W., Li, J.: Detection of the mobile object with camouflage color under dynamic background based on optical flow. Procedia Eng. 15, 2201\u20132205 (2011)","journal-title":"Procedia Eng."},{"key":"2611_CR19","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":"2611_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108414","volume":"123","author":"GP Ji","year":"2022","unstructured":"Ji, G.P., Zhu, L., Zhuge, M., Fu, K.: Fast camouflaged object detection via edge-based reversible re-calibration network. Pattern Recogn. 123, 108414 (2022)","journal-title":"Pattern Recogn."},{"key":"2611_CR21","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"2611_CR22","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.cviu.2019.04.006","volume":"184","author":"TN Le","year":"2019","unstructured":"Le, T.N., Nguyen, T.V., Nie, Z., Tran, M.T., Sugimoto, A.: Anabranch network for camouflaged object segmentation. Comput. Vis. Image Underst. 184, 45\u201356 (2019)","journal-title":"Comput. Vis. Image Underst."},{"key":"2611_CR23","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.neucom.2019.09.107","volume":"408","author":"X Le","year":"2020","unstructured":"Le, X., Mei, J., Zhang, H., Zhou, B., Xi, J.: A learning-based approach for surface defect detection using small image datasets. Neurocomputing 408, 112\u2013120 (2020)","journal-title":"Neurocomputing"},{"key":"2611_CR24","doi-asserted-by":"crossref","unstructured":"Li, A., Zhang, J., Lv, Y., Liu, B., Zhang, T., Dai, Y.: Uncertainty-aware joint salient object and camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10071\u201310081 (2021)","DOI":"10.1109\/CVPR46437.2021.00994"},{"key":"2611_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neucom.2020.05.027","volume":"409","author":"D Liu","year":"2020","unstructured":"Liu, D., Cui, Y., Chen, Y., Zhang, J., Fan, B.: Video object detection for autonomous driving: Motion-aid feature calibration. Neurocomputing 409, 1\u201311 (2020)","journal-title":"Neurocomputing"},{"key":"2611_CR26","doi-asserted-by":"crossref","unstructured":"Liu, D., Cui, Y., Tan, W., Chen, Y.: Sg-net: Spatial granularity network for one-stage video instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9816\u20139825 (2021)","DOI":"10.1109\/CVPR46437.2021.00969"},{"issue":"9","key":"2611_CR27","doi-asserted-by":"publisher","first-page":"4204","DOI":"10.1109\/TIP.2012.2200492","volume":"21","author":"Z Liu","year":"2012","unstructured":"Liu, Z., Huang, K., Tan, T.: Foreground object detection using top-down information based on em framework. IEEE Trans. Image Process. 21(9), 4204\u20134217 (2012)","journal-title":"IEEE Trans. Image Process."},{"key":"2611_CR28","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":"2611_CR29","doi-asserted-by":"crossref","unstructured":"Lv, Y., Zhang, J., Dai, Y., Li, A., Liu, B., Barnes, N., Fan, D.P.: Simultaneously localize, segment and rank the camouflaged objects. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11591\u201311601 (2021)","DOI":"10.1109\/CVPR46437.2021.01142"},{"key":"2611_CR30","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":"2611_CR31","doi-asserted-by":"crossref","unstructured":"Mei, H., Ji, G.P., Wei, Z., Yang, X., Wei, X., Fan, D.P.: Camouflaged object segmentation with distraction mining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8772\u20138781 (2021)","DOI":"10.1109\/CVPR46437.2021.00866"},{"issue":"4","key":"2611_CR32","doi-asserted-by":"publisher","first-page":"152","DOI":"10.5539\/mas.v5n4p152","volume":"5","author":"Y Pan","year":"2011","unstructured":"Pan, Y., Chen, Y., Fu, Q., Zhang, P., Xu, X.: Study on the camouflaged target detection method based on 3d convexity. Mod. Appl. Sci. 5(4), 152 (2011)","journal-title":"Mod. Appl. Sci."},{"key":"2611_CR33","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":"2611_CR34","unstructured":"Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al.: Pytorch: an imperative style, high-performance deep learning library. Advances in neural information processing systems 32 (2019)"},{"key":"2611_CR35","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, pp. 733\u2013740. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"2611_CR36","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":"2611_CR37","doi-asserted-by":"crossref","unstructured":"Sengottuvelan, P., Wahi, A., Shanmugam, A.: Performance of decamouflaging through exploratory image analysis. In: 2008 First International Conference on Emerging Trends in Engineering and Technology, pp. 6\u201310. IEEE (2008)","DOI":"10.1109\/ICETET.2008.232"},{"key":"2611_CR38","unstructured":"Skurowski, P., Abdulameer, H., B\u0142aszczyk, J., Depta, T., Kornacki, A., Kozie\u0142, P.: Animal camouflage analysis: Chameleon database. Unpublished manuscript 2(6), 7 (2018)"},{"key":"2611_CR39","doi-asserted-by":"crossref","unstructured":"Sun, Y., Chen, G., Zhou, T., Zhang, Y., Liu, N.: Context-aware cross-level fusion network for camouflaged object detection. arXiv preprint arXiv:2105.12555 (2021)","DOI":"10.24963\/ijcai.2021\/142"},{"key":"2611_CR40","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30 (2017)"},{"issue":"5","key":"2611_CR41","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1007\/s00371-020-01855-z","volume":"37","author":"D Wang","year":"2021","unstructured":"Wang, D., Hu, G., Lyu, C.: Frnet: an end-to-end feature refinement neural network for medical image segmentation. Vis. Comput. 37(5), 1101\u20131112 (2021)","journal-title":"Vis. Comput."},{"key":"2611_CR42","doi-asserted-by":"publisher","first-page":"5364","DOI":"10.1109\/TIE.2021.3078379","volume":"69","author":"K Wang","year":"2021","unstructured":"Wang, K., Bi, H., Zhang, Y., Zhang, C., Liu, Z., Zheng, S.: D 2 c-net: a dual-branch, dual-guidance and cross-refine network for camouflaged object detection. IEEE Trans. Ind. Electron. 69, 5364 (2021)","journal-title":"IEEE Trans. Ind. Electron."},{"key":"2611_CR43","doi-asserted-by":"crossref","unstructured":"Wang, W., Xie, E., Li, X., Fan, D.P., Song, K., Liang, D., Lu, T., Luo, P., Shao, L.: Pyramid vision transformer: A versatile backbone for dense prediction without convolutions. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 568\u2013578 (2021)","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"2611_CR44","doi-asserted-by":"crossref","unstructured":"Wang, X., Girshick, R., Gupta, A., He, K.: Non-local neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 7794\u20137803 (2018)","DOI":"10.1109\/CVPR.2018.00813"},{"key":"2611_CR45","doi-asserted-by":"crossref","unstructured":"Wang, X., Wang, W., Bi, H., Wang, K.: Reverse collaborative fusion model for co-saliency detection. The Visual Computer pp. 1\u201311 (2021)","DOI":"10.1007\/s00371-021-02231-1"},{"key":"2611_CR46","first-page":". 12321","volume":"34","author":"J Wei","year":"2020","unstructured":"Wei, J., Wang, S., Huang, Q.: F$$^3$$net: fusion, feedback and focus for salient object detection. Proc. AAAI Conf. Artif. Intell. 34, . 12321-12328 (2020)","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"2611_CR47","doi-asserted-by":"publisher","first-page":"3113","DOI":"10.1109\/TIP.2021.3058783","volume":"30","author":"YH Wu","year":"2021","unstructured":"Wu, Y.H., Gao, S.H., Mei, J., Xu, J., Fan, D.P., Zhang, R.G., Cheng, M.M.: Jcs: an explainable covid-19 diagnosis system by joint classification and segmentation. IEEE Trans. Image Process. 30, 3113\u20133126 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"2611_CR48","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":"2611_CR49","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":"2611_CR50","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-022-02414-4","author":"H Xiao","year":"2022","unstructured":"Xiao, H., Ran, Z., Mabu, S., Li, Y., Li, L.: Saunet++: an automatic segmentation model of covid-19 lesion from ct slices. Vis. Comput. (2022). https:\/\/doi.org\/10.1007\/s00371-022-02414-4","journal-title":"Vis. Comput."},{"key":"2611_CR51","doi-asserted-by":"publisher","first-page":"43290","DOI":"10.1109\/ACCESS.2021.3064443","volume":"9","author":"J Yan","year":"2021","unstructured":"Yan, J., Le, T.N., Nguyen, K.D., Tran, M.T., Do, T.T., Nguyen, T.V.: Mirrornet: bio-inspired camouflaged object segmentation. IEEE Access 9, 43290\u201343300 (2021)","journal-title":"IEEE Access"},{"key":"2611_CR52","doi-asserted-by":"crossref","unstructured":"Yang, F., Zhai, Q., Li, X., Huang, R., Luo, A., Cheng, H., Fan, D.P.: Uncertainty-guided transformer reasoning for camouflaged object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4146\u20134155 (2021)","DOI":"10.1109\/ICCV48922.2021.00411"},{"key":"2611_CR53","unstructured":"Youwei, P., Xiaoqi, Z., Tian-Zhu, X., Lihe, Z., Huchuan, L.: Zoom in and out: A mixed-scale triplet network for camouflaged object detection. arXiv preprint arXiv:2203.02688 (2022)"},{"key":"2611_CR54","doi-asserted-by":"crossref","unstructured":"Yuan, L., Chen, Y., Wang, T., Yu, W., Shi, Y., Jiang, Z.H., Tay, F.E., Feng, J., Yan, S.: Tokens-to-token vit: Training vision transformers from scratch on imagenet. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 558\u2013567 (2021)","DOI":"10.1109\/ICCV48922.2021.00060"},{"key":"2611_CR55","doi-asserted-by":"crossref","unstructured":"Zhai, Q., Li, X., Yang, F., Chen, C., Cheng, H., Fan, D.P.: Mutual graph learning for camouflaged object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12997\u201313007 (2021)","DOI":"10.1109\/CVPR46437.2021.01280"},{"issue":"5","key":"2611_CR56","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1007\/s00371-020-01854-0","volume":"37","author":"X Zhang","year":"2021","unstructured":"Zhang, X., Wang, X., Gu, C.: Online multi-object tracking with pedestrian re-identification and occlusion processing. Vis. Comput. 37(5), 1089\u20131099 (2021)","journal-title":"Vis. Comput."},{"key":"2611_CR57","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-022-02404-6","author":"Y Zhang","year":"2022","unstructured":"Zhang, Y., Han, S., Zhang, Z., Wang, J., Bi, H.: Cf-gan: cross-domain feature fusion generative adversarial network for text-to-image synthesis. Vis. Comput. (2022). https:\/\/doi.org\/10.1007\/s00371-022-02404-6","journal-title":"Vis. Comput."},{"key":"2611_CR58","doi-asserted-by":"crossref","unstructured":"Zhao, J.X., Liu, J.J., Fan, D.P., Cao, Y., Yang, J., Cheng, M.M.: Egnet: Edge guidance network for salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp. 8779\u20138788 (2019)","DOI":"10.1109\/ICCV.2019.00887"},{"key":"2611_CR59","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108644","volume":"127","author":"M Zhuge","year":"2022","unstructured":"Zhuge, M., Lu, X., Guo, Y., Cai, Z., Chen, S.: Cubenet: X-shape connection for camouflaged object detection. Pattern Recogn. 127, 108644 (2022)","journal-title":"Pattern Recogn."}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02611-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-022-02611-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-022-02611-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:05:50Z","timestamp":1695978350000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-022-02611-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":59,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["2611"],"URL":"https:\/\/doi.org\/10.1007\/s00371-022-02611-1","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,18]]},"assertion":[{"value":"24 June 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 July 2022","order":2,"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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}