{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T05:16:18Z","timestamp":1733548578604,"version":"3.30.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100002561","name":"Soongsil University","doi-asserted-by":"publisher","award":["New Professor Support Research of 2021"],"id":[{"id":"10.13039\/501100002561","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pattern Anal Applic"],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1007\/s10044-024-01379-5","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T17:48:39Z","timestamp":1733507319000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SA-DETR: Saliency Attention-based DETR for salient object detection"],"prefix":"10.1007","volume":"28","author":[{"given":"Kwangwoon","family":"Nam","sequence":"first","affiliation":[]},{"given":"Jeeheon","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Heeyeon","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Minyoung","family":"Chung","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"1379_CR1","doi-asserted-by":"crossref","unstructured":"Achanta R, Hemami S, Estrada F, et al (2009) Frequency-tuned salient region detection. In: 2009 IEEE conference on computer vision and pattern recognition. IEEE, pp 1597\u20131604","DOI":"10.1109\/CVPR.2009.5206596"},{"key":"1379_CR2","doi-asserted-by":"publisher","first-page":"1055","DOI":"10.1007\/s11760-019-01445-0","volume":"13","author":"K Brahim","year":"2019","unstructured":"Brahim K, Kalboussi R, Abdellaoui M et al (2019) Spatio-temporal saliency detection using objectness measure. Signal, Image Video Process 13:1055\u20131062","journal-title":"Signal, Image Video Process"},{"key":"1379_CR3","doi-asserted-by":"crossref","unstructured":"Carion N, Massa F, Synnaeve G, et al (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. Springer, pp 213\u2013229","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"1379_CR4","unstructured":"Chen Q, Wang J, Han C et al (2022) Group detr v2: Strong object detector with encoder-decoder pretraining. arXiv preprint arXiv:2211.03594"},{"key":"1379_CR5","doi-asserted-by":"crossref","unstructured":"Cheng MM, Zhang Z, Lin WY et al (2014) Bing: Binarized normed gradients for objectness estimation at 300fps. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3286\u20133293","DOI":"10.1109\/CVPR.2014.414"},{"key":"1379_CR6","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A et al (2020) An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929"},{"key":"1379_CR7","doi-asserted-by":"crossref","unstructured":"Fan DP, Cheng MM, Liu Y, et al (2017) Structure-measure: a new way to evaluate foreground maps. In: Proceedings of the IEEE international conference on computer vision, pp 4548\u20134557","DOI":"10.1109\/ICCV.2017.487"},{"key":"1379_CR8","doi-asserted-by":"crossref","unstructured":"Fan DP, Gong C, Cao Y et al (2018) Enhanced-alignment measure for binary foreground map evaluation. arXiv preprint arXiv:1805.10421","DOI":"10.24963\/ijcai.2018\/97"},{"issue":"2","key":"1379_CR9","doi-asserted-by":"publisher","first-page":"2344","DOI":"10.1109\/TPAMI.2022.3166451","volume":"45","author":"DP Fan","year":"2022","unstructured":"Fan DP, Zhang J, Xu G et al (2022) Salient objects in clutter. IEEE Trans Pattern Anal Mach Intell 45(2):2344\u20132366","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1379_CR10","doi-asserted-by":"crossref","unstructured":"Fang Y, Wang W, Xie B et al (2022) Eva: Exploring the limits of masked visual representation learning at scale. arXiv preprint arXiv:2211.07636","DOI":"10.1109\/CVPR52729.2023.01855"},{"key":"1379_CR11","doi-asserted-by":"crossref","unstructured":"Harel J, Koch C, Perona P (2006) Graph-based visual saliency. Advances in neural information processing systems 19","DOI":"10.7551\/mitpress\/7503.003.0073"},{"issue":"4","key":"1379_CR12","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1109\/TPAMI.2018.2815688","volume":"41","author":"Q Hou","year":"2019","unstructured":"Hou Q, Cheng MM, Hu X et al (2019) Deeply supervised salient object detection with short connections. IEEE TPAMI 41(4):815\u2013828. https:\/\/doi.org\/10.1109\/TPAMI.2018.2815688","journal-title":"IEEE TPAMI"},{"key":"1379_CR13","doi-asserted-by":"crossref","unstructured":"Hou X, Zhang L (2007) Saliency detection: A spectral residual approach. In: 2007 IEEE Conference on computer vision and pattern recognition. IEEE, pp 1\u20138","DOI":"10.1109\/CVPR.2007.383267"},{"issue":"11","key":"1379_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 (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254\u20131259","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1379_CR15","doi-asserted-by":"crossref","unstructured":"Li G, Yu Y (2016) Deep contrast learning for salient object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 478\u2013487","DOI":"10.1109\/CVPR.2016.58"},{"key":"1379_CR16","doi-asserted-by":"crossref","unstructured":"Li Y, Hou X, Koch C et al (2014) The secrets of salient object segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 280\u2013287","DOI":"10.1109\/CVPR.2014.43"},{"key":"1379_CR17","doi-asserted-by":"crossref","unstructured":"Liu JJ, Hou Q, Cheng MM et al (2019) 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","DOI":"10.1109\/CVPR.2019.00404"},{"key":"1379_CR18","doi-asserted-by":"crossref","unstructured":"Liu N, Zhang N, Wan K et al (2021) Visual saliency transformer. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4722\u20134732","DOI":"10.1109\/ICCV48922.2021.00468"},{"key":"1379_CR19","doi-asserted-by":"crossref","unstructured":"Liu Y, Cheng MM, Hu X et al (2017) Richer convolutional features for edge detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3000\u20133009","DOI":"10.1109\/CVPR.2017.622"},{"key":"1379_CR20","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y et al (2021) Swin transformer: Hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 10012\u201310022","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"1379_CR21","doi-asserted-by":"crossref","unstructured":"Luo Z, Mishra A, Achkar A et al (2017) Non-local deep features for salient object detection. In: Proceedings of the IEEE Conference on computer vision and pattern recognition, pp 6609\u20136617","DOI":"10.1109\/CVPR.2017.698"},{"key":"1379_CR22","doi-asserted-by":"crossref","unstructured":"Nguyen T (2015) Salient object detection via objectness proposals. In: Proceedings of the AAAI Conference on Artificial Intelligence","DOI":"10.1609\/aaai.v29i1.9279"},{"key":"1379_CR23","unstructured":"Pan J, Sayrol E, Nieto XG et al (2017) Salgan: Visual saliency prediction with adversarial networks. In: CVPR scene understanding workshop (SUNw)"},{"key":"1379_CR24","doi-asserted-by":"crossref","unstructured":"Perazzi F, Kr\u00e4henb\u00fchl P, Pritch Y et al (2012) Saliency filters: contrast based filtering for salient region detection. In: 2012 IEEE conference on computer vision and pattern recognition. IEEE, pp 733\u2013740","DOI":"10.1109\/CVPR.2012.6247743"},{"key":"1379_CR25","doi-asserted-by":"crossref","unstructured":"Qin X, Zhang Z, Huang C et al (2019) Basnet: Boundary-aware salient object detection. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7479\u20137489","DOI":"10.1109\/CVPR.2019.00766"},{"key":"1379_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107404","volume":"106","author":"X Qin","year":"2020","unstructured":"Qin X, Zhang Z, Huang C et al (2020) U2-net: Going deeper with nested u-structure for salient object detection. Pattern Recognit 106:107404","journal-title":"Pattern Recognit"},{"key":"1379_CR27","doi-asserted-by":"crossref","unstructured":"Srivatsa RS, Babu RV (2015) Salient object detection via objectness measure. In: 2015 IEEE international conference on image processing (ICIP). IEEE, pp 4481\u20134485","DOI":"10.1109\/ICIP.2015.7351654"},{"key":"1379_CR28","unstructured":"Vaswani A, Shazeer N, Parmar N et al (2017) Attention is all you need. Advances in neural information processing systems 30"},{"key":"1379_CR29","doi-asserted-by":"crossref","unstructured":"Wang L, Lu H, Wang Y et al (2017) Learning to detect salient objects with image-level supervision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 136\u2013145","DOI":"10.1109\/CVPR.2017.404"},{"key":"1379_CR30","doi-asserted-by":"crossref","unstructured":"Wei J, Wang S, Huang Q (2020) $$\\text{F}^3$$net: fusion, feedback and focus for salient object detection. In: Proceedings of the AAAI conference on artificial intelligence, pp 12321\u201312328","DOI":"10.1609\/aaai.v34i07.6916"},{"key":"1379_CR31","doi-asserted-by":"crossref","unstructured":"Wu Z, Su L, Huang Q (2019) Stacked cross refinement network for edge-aware salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 7264\u20137273","DOI":"10.1109\/ICCV.2019.00736"},{"key":"1379_CR32","doi-asserted-by":"crossref","unstructured":"Yang C, Zhang L, Lu H et al (2013) Saliency detection via graph-based manifold ranking. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3166\u20133173","DOI":"10.1109\/CVPR.2013.407"},{"key":"1379_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2022.103514","volume":"126","author":"SSA Zaidi","year":"2022","unstructured":"Zaidi SSA, Ansari MS, Aslam A et al (2022) A survey of modern deep learning based object detection models. Digit Signal Process 126:103514","journal-title":"Digit Signal Process"},{"issue":"9","key":"1379_CR34","first-page":"5761","volume":"44","author":"J Zhang","year":"2021","unstructured":"Zhang J, Fan DP, Dai Y et al (2021) Uncertainty inspired rgb-d saliency detection. IEEE Trans Pattern Anal Mach Intell 44(9):5761\u20135779","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1379_CR35","doi-asserted-by":"crossref","unstructured":"Zhang P, Wang D, Lu H et al (2017) Learning uncertain convolutional features for accurate saliency detection. In: Proceedings of the IEEE International Conference on computer vision, pp 212\u2013221","DOI":"10.1109\/ICCV.2017.32"},{"key":"1379_CR36","doi-asserted-by":"crossref","unstructured":"Zhao JX, Liu JJ, Fan DP et al (2019) Egnet: Edge guidance network for salient object detection. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 8779\u20138788","DOI":"10.1109\/ICCV.2019.00887"},{"issue":"3","key":"1379_CR37","first-page":"3738","volume":"45","author":"M Zhuge","year":"2022","unstructured":"Zhuge M, Fan DP, Liu N et al (2022) Salient object detection via integrity learning. IEEE Trans Pattern Anal Mach Intell 45(3):3738\u201352","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1379_CR38","doi-asserted-by":"crossref","unstructured":"Zong Z, Song G, Liu Y (2022) Detrs with collaborative hybrid assignments training. arXiv preprint arXiv:2211.12860","DOI":"10.1109\/ICCV51070.2023.00621"}],"container-title":["Pattern Analysis and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-024-01379-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10044-024-01379-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10044-024-01379-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T18:03:45Z","timestamp":1733508225000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10044-024-01379-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,6]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["1379"],"URL":"https:\/\/doi.org\/10.1007\/s10044-024-01379-5","relation":{},"ISSN":["1433-7541","1433-755X"],"issn-type":[{"value":"1433-7541","type":"print"},{"value":"1433-755X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,6]]},"assertion":[{"value":"11 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 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 authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical and informed consent for data used"}}],"article-number":"5"}}