{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T18:45:08Z","timestamp":1747248308202,"version":"3.37.3"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"The Natural Science Foundation of Hebei Province","award":["F2019201451"],"award-info":[{"award-number":["F2019201451"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pattern Anal Applic"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s10044-023-01185-5","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T18:02:16Z","timestamp":1688061736000},"page":"957-967","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Hybrid two-stage cascade for instance segmentation of overlapping objects"],"prefix":"10.1007","volume":"26","author":[{"given":"Yakun","family":"Yang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2070-465X","authenticated-orcid":false,"given":"Wenjie","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Xuedong","family":"Tian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"key":"1185_CR1","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Doll\u00e1r P, Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 2961\u20132969","DOI":"10.1109\/ICCV.2017.322"},{"key":"1185_CR2","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster r-cnn: towards real-time object detection with region proposal networks. Advances in neural information processing systems 28"},{"key":"1185_CR3","doi-asserted-by":"crossref","unstructured":"Chen L-C, Hermans A, Papandreou G, Schroff F, Wang P, Adam H (2018) Masklab: Instance segmentation by refining object detection with semantic and direction features. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4013\u20134022","DOI":"10.1109\/CVPR.2018.00422"},{"key":"1185_CR4","doi-asserted-by":"crossref","unstructured":"Huang Z, Huang L, Gong Y, Huang C, Wang X (2019) Mask scoring r-cnn. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 6409\u20136418","DOI":"10.1109\/CVPR.2019.00657"},{"key":"1185_CR5","doi-asserted-by":"crossref","unstructured":"Chen X, Girshick R, He K, Doll\u00e1r P (2019) Tensormask: A foundation for dense object segmentation. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 2061\u20132069","DOI":"10.1109\/ICCV.2019.00215"},{"key":"1185_CR6","doi-asserted-by":"crossref","unstructured":"Cheng T, Wang X, Huang L, Liu W (2020) Boundary-preserving mask r-cnn. In: European conference on computer vision, pp 660\u2013676. Springer","DOI":"10.1007\/978-3-030-58568-6_39"},{"key":"1185_CR7","doi-asserted-by":"crossref","unstructured":"Liu S, Qi L, Qin H, Shi J, Jia J (2018) Path aggregation network for instance segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 8759\u20138768","DOI":"10.1109\/CVPR.2018.00913"},{"key":"1185_CR8","doi-asserted-by":"crossref","unstructured":"Lee Y, Park J (2020) Centermask: real-time anchor-free instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 13906\u201313915","DOI":"10.1109\/CVPR42600.2020.01392"},{"key":"1185_CR9","doi-asserted-by":"crossref","unstructured":"Wang Y, Xu Z, Shen H, Cheng B, Yang L (2020) Centermask: single shot instance segmentation with point representation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9313\u20139321","DOI":"10.1109\/CVPR42600.2020.00933"},{"key":"1185_CR10","doi-asserted-by":"crossref","unstructured":"Xie E, Sun P, Song X, Wang W, Liu X, Liang D, Shen C, Luo P (2020) Polarmask: Single shot instance segmentation with polar representation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12193\u201312202","DOI":"10.1109\/CVPR42600.2020.01221"},{"key":"1185_CR11","doi-asserted-by":"crossref","unstructured":"Chen H, Sun K, Tian Z, Shen C, Huang Y, Yan Y (2020) Blendmask: top-down meets bottom-up for instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8573\u20138581","DOI":"10.1109\/CVPR42600.2020.00860"},{"key":"1185_CR12","doi-asserted-by":"crossref","unstructured":"Duan K, Bai S, Xie L, Qi H, Huang Q, Tian Q (2019) Centernet: Keypoint triplets for object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 6569\u20136578. IEEE","DOI":"10.1109\/ICCV.2019.00667"},{"key":"1185_CR13","doi-asserted-by":"crossref","unstructured":"Tian Z, Shen C, Chen H, He T (2019) Fcos: fully convolutional one-stage object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 9627\u20139636","DOI":"10.1109\/ICCV.2019.00972"},{"key":"1185_CR14","doi-asserted-by":"crossref","unstructured":"Chen K, Pang J, Wang J, Xiong Y, Li X, Sun S, Feng W, Liu Z, Shi J, Ouyang W, et al (2019) Hybrid task cascade for instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4974\u20134983","DOI":"10.1109\/CVPR.2019.00511"},{"key":"1185_CR15","doi-asserted-by":"crossref","unstructured":"Ding H, Qiao S, Yuille A, Shen W (2021) Deeply shape-guided cascade for instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8278\u20138288","DOI":"10.1109\/CVPR46437.2021.00818"},{"key":"1185_CR16","doi-asserted-by":"crossref","unstructured":"Bolya D, Zhou C, Xiao F, Lee YJ (2019) Yolact: Real-time instance segmentation. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 9157\u20139166","DOI":"10.1109\/ICCV.2019.00925"},{"key":"1185_CR17","doi-asserted-by":"crossref","unstructured":"Bolya D, Zhou C, Xiao F, Lee YJ (2020) Yolact++: Better real-time instance segmentation. IEEE transactions on pattern analysis and machine intelligence","DOI":"10.1109\/ICCV.2019.00925"},{"key":"1185_CR18","doi-asserted-by":"crossref","unstructured":"Wang X, Kong T, Shen C, Jiang Y, Li L (2020) Solo: segmenting objects by locations. In: European conference on computer vision, pp 649\u2013665. Springer","DOI":"10.1007\/978-3-030-58523-5_38"},{"key":"1185_CR19","first-page":"17721","volume":"33","author":"X Wang","year":"2020","unstructured":"Wang X, Zhang R, Kong T, Li L, Shen C (2020) Solov2: dynamic and fast instance segmentation. Adv Neural Inf Process Syst 33:17721\u201317732","journal-title":"Adv Neural Inf Process Syst"},{"key":"1185_CR20","doi-asserted-by":"crossref","unstructured":"Peng S, Jiang W, Pi H, Li X, Bao H, Zhou X (2020) Deep snake for real-time instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8533\u20138542","DOI":"10.1109\/CVPR42600.2020.00856"},{"key":"1185_CR21","doi-asserted-by":"crossref","unstructured":"Ling H, Gao J, Kar A, Chen W, Fidler S (2019) Fast interactive object annotation with curve-GCN. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5257\u20135266","DOI":"10.1109\/CVPR.2019.00540"},{"key":"1185_CR22","doi-asserted-by":"crossref","unstructured":"Xu W, Wang H, Qi F, Lu C (2019) Explicit shape encoding for real-time instance segmentation. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 5168\u20135177","DOI":"10.1109\/ICCV.2019.00527"},{"key":"1185_CR23","doi-asserted-by":"crossref","unstructured":"Riaz HUM, Benbarka N, Zell A (2021) Fouriernet: Compact mask representation for instance segmentation using differentiable shape decoders. In: 2020 25th international conference on pattern recognition (ICPR), pp 7833\u20137840. IEEE","DOI":"10.1109\/ICPR48806.2021.9413048"},{"issue":"5","key":"1185_CR24","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1109\/TPAMI.2019.2956516","volume":"43","author":"Z Cai","year":"2019","unstructured":"Cai Z, Vasconcelos N (2019) Cascade r-cnn: high quality object detection and instance segmentation. IEEE Trans Pattern Anal Mach Intell 43(5):1483\u20131498","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1185_CR25","doi-asserted-by":"crossref","unstructured":"Cai Z, Vasconcelos N (2018) Cascade r-cnn: Delving into high quality object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 6154\u20136162","DOI":"10.1109\/CVPR.2018.00644"},{"key":"1185_CR26","doi-asserted-by":"crossref","unstructured":"Zhang G, Lu X, Tan J, Li J, Zhang Z, Li Q, Hu X (2021) Refinemask: towards high-quality instance segmentation with fine-grained features. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 6861\u20136869","DOI":"10.1109\/CVPR46437.2021.00679"},{"key":"1185_CR27","doi-asserted-by":"crossref","unstructured":"Liu S, Jia J, Fidler S, Urtasun R (2017) Sgn: Sequential grouping networks for instance segmentation. In: Proceedings of the IEEE international conference on computer vision, pp 3496\u20133504","DOI":"10.1109\/ICCV.2017.378"},{"key":"1185_CR28","doi-asserted-by":"crossref","unstructured":"Gao N, Shan Y, Wang Y, Zhao X, Yu Y, Yang M, Huang K (2019) Ssap: Single-shot instance segmentation with affinity pyramid. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 642\u2013651","DOI":"10.1109\/ICCV.2019.00073"},{"key":"1185_CR29","doi-asserted-by":"crossref","unstructured":"De Brabandere B, Neven D, Van Gool L (2017) Semantic instance segmentation with a discriminative loss function. arXiv preprint arXiv:1708.02551","DOI":"10.1109\/CVPRW.2017.66"},{"key":"1185_CR30","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Adv Neural Inf Process Syst 30"},{"key":"1185_CR31","first-page":"21898","volume":"34","author":"B Dong","year":"2021","unstructured":"Dong B, Zeng F, Wang T, Zhang X, Wei Y (2021) Solq: Segmenting objects by learning queries. Adv Neural Inf Process Syst 34:21898\u201321909","journal-title":"Adv Neural Inf Process Syst"},{"key":"1185_CR32","doi-asserted-by":"crossref","unstructured":"Carion N, Massa F, Synnaeve G, Usunier N, Kirillov A, Zagoruyko S (2020) End-to-end object detection with transformers. In: Computer vision\u2013ECCV 2020: 16th European conference, Glasgow, UK, August 23\u201328, 2020, proceedings, Part I 16, pp. 213\u2013229. Springer","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"1185_CR33","doi-asserted-by":"crossref","unstructured":"Fang Y, Yang S, Wang X, Li Y, Fang C, Shan Y, Feng B, Liu W (2021) Instances as queries. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 6910\u20136919","DOI":"10.1109\/ICCV48922.2021.00683"},{"key":"1185_CR34","doi-asserted-by":"crossref","unstructured":"Sun P, Zhang R, Jiang Y, Kong T, Xu C, Zhan W, Tomizuka M, Li L, Yuan Z, Wang C, et al (2021) Sparse r-cnn: End-to-end object detection with learnable proposals. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 14454\u201314463","DOI":"10.1109\/CVPR46437.2021.01422"},{"key":"1185_CR35","doi-asserted-by":"crossref","unstructured":"Guo R, Niu D, Qu L, Li Z (2021) Sotr: segmenting objects with transformers. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 7157\u20137166","DOI":"10.1109\/ICCV48922.2021.00707"},{"key":"1185_CR36","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1185_CR37","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee J-Y, Kweon IS (2018) Cbam: convolutional block attention module. In: Proceedings of the European conference on computer vision (ECCV), pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1185_CR38","doi-asserted-by":"crossref","unstructured":"Lin T-Y, Doll\u00e1r P, Girshick R, He K, Hariharan B, Belongie S (2017) Feature pyramid networks for object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2117\u20132125","DOI":"10.1109\/CVPR.2017.106"},{"key":"1185_CR39","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"1185_CR40","doi-asserted-by":"crossref","unstructured":"Chen Q, Wang Y, Yang T, Zhang X, Cheng J, Sun J (2021) You only look one-level feature. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 13039\u201313048. IEEE","DOI":"10.1109\/CVPR46437.2021.01284"},{"issue":"4","key":"1185_CR41","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"L-C Chen","year":"2017","unstructured":"Chen L-C, Papandreou G, Kokkinos I, Murphy K, Yuille AL (2017) Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans Pattern Anal Mach Intell 40(4):834\u2013848","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1185_CR42","unstructured":"Zhang H, Zu K, Lu J, Zou Y, Meng D (2021) Epsanet: An efficient pyramid squeeze attention block on convolutional neural network. arXiv preprint arXiv:2105.14447"},{"key":"1185_CR43","doi-asserted-by":"crossref","unstructured":"Lin T-Y, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Doll\u00e1r P, Zitnick CL (2014) Microsoft coco: common objects in context. In: European conference on computer vision, pp 740\u2013755. Springer","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1185_CR44","unstructured":"Chen K, Wang J, Pang J, Cao Y, Xiong Y, Li X, Sun S, Feng W, Liu Z, Xu J, et al (2019) Mmdetection: open mmlab detection toolbox and benchmark. arXiv preprint arXiv:1906.07155"},{"key":"1185_CR45","doi-asserted-by":"crossref","unstructured":"Xie S, Girshick R, Doll\u00e1r P, Tu Z, He K (2017) Aggregated residual transformations for deep neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1492\u20131500","DOI":"10.1109\/CVPR.2017.634"},{"key":"1185_CR46","doi-asserted-by":"crossref","unstructured":"Sandler M, Howard A, Zhu M, Zhmoginov A, Chen L-C (2018) Mobilenetv2: Inverted residuals and linear bottlenecks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4510\u20134520","DOI":"10.1109\/CVPR.2018.00474"},{"key":"1185_CR47","unstructured":"Sun K, Zhao Y, Jiang B, Cheng T, Xiao B, Liu D, Mu Y, Wang X, Liu W, Wang J (2019) High-resolution representations for labeling pixels and regions. arXiv preprint arXiv:1904.04514"},{"key":"1185_CR48","unstructured":"Chen L-C, Papandreou G, Schroff F, Adam H (2017) Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587"},{"key":"1185_CR49","doi-asserted-by":"crossref","unstructured":"Tian Z, Shen C, Chen H (2020) Conditional convolutions for instance segmentation. In: Computer vision\u2013ECCV 2020: 16th European conference, Glasgow, UK, August 23\u201328, 2020, proceedings, Part I 16, pp 282\u2013298. Springer","DOI":"10.1007\/978-3-030-58452-8_17"},{"key":"1185_CR50","doi-asserted-by":"crossref","unstructured":"Kirillov A, Wu Y, He K, Girshick R (2020) Pointrend: image segmentation as rendering. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9799\u20139808","DOI":"10.1109\/CVPR42600.2020.00982"},{"key":"1185_CR51","doi-asserted-by":"crossref","unstructured":"Tang C, Chen H, Li X, Li J, Zhang Z, Hu X (2021) Look closer to segment better: Boundary patch refinement for instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 13926\u201313935","DOI":"10.1109\/CVPR46437.2021.01371"}],"container-title":["Pattern Analysis and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-023-01185-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10044-023-01185-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-023-01185-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,22]],"date-time":"2023-07-22T14:12:04Z","timestamp":1690035124000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10044-023-01185-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,29]]},"references-count":51,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["1185"],"URL":"https:\/\/doi.org\/10.1007\/s10044-023-01185-5","relation":{},"ISSN":["1433-7541","1433-755X"],"issn-type":[{"type":"print","value":"1433-7541"},{"type":"electronic","value":"1433-755X"}],"subject":[],"published":{"date-parts":[[2023,6,29]]},"assertion":[{"value":"5 January 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 June 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2023","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 potential conflict of interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}