{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T00:58:32Z","timestamp":1742950712255,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":16,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811681288"},{"type":"electronic","value":"9789811681295"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-8129-5_74","type":"book-chapter","created":{"date-parts":[[2022,2,11]],"date-time":"2022-02-11T17:02:58Z","timestamp":1644598978000},"page":"481-486","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Survey on Loss Function for Face Recognition"],"prefix":"10.1007","author":[{"given":"Seng Chun","family":"Hoo","sequence":"first","affiliation":[]},{"given":"Adeshina Sirajdin","family":"Olagoke","sequence":"additional","affiliation":[]},{"given":"Haidi","family":"Ibrahim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,2,11]]},"reference":[{"key":"74_CR1","doi-asserted-by":"publisher","first-page":"102805","DOI":"10.1016\/j.cviu.2019.102805","volume":"189","author":"G Guo","year":"2019","unstructured":"Guo, G., Zhang, N.: A survey on deep learning based face recognition. Comput. Vis. Image Underst. 189, 102805 (2019)","journal-title":"Comput. Vis. Image Underst."},{"key":"74_CR2","unstructured":"Liu, W., Wen, Y., Yu, Z., Yang, M.: Large-margin softmax loss for convolutional neural networks. In: International Conference on Machine Learning, vol. 2, no. 3, p. 7 (2016)"},{"issue":"65","key":"74_CR3","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MSP.2017.2732900","volume":"34","author":"J Lu","year":"2017","unstructured":"Lu, J., Hu, J., Zhou, J.: Deep metric learning for visual understanding: an overview of recent advances. IEEE Sig. Process. Mag. 34(65), 76\u201384 (2017)","journal-title":"IEEE Sig. Process. Mag."},{"key":"74_CR4","unstructured":"Sun, Y., Chen, Y., Wang, X., Tang, X.: Deep Learning face representation by joint identification-verification. In: Advances in Neural Information Processing Systems, pp. 1988\u20131996 (2014)"},{"key":"74_CR5","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: FaceNet: a unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"74_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1007\/978-3-319-46478-7_31","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Y Wen","year":"2016","unstructured":"Wen, Y., Zhang, K., Li, Z., Qiao, Y.: A discriminative feature learning approach for deep face recognition. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9911, pp. 499\u2013515. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46478-7_31"},{"key":"74_CR7","doi-asserted-by":"crossref","unstructured":"Deng, J., Zhou, Y., Zafeiriou, S.: Marginal loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 60\u201368 (2017)","DOI":"10.1109\/CVPRW.2017.251"},{"key":"74_CR8","doi-asserted-by":"crossref","unstructured":"Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., Song, L.: SphereFace: deep hypersphere embedding for face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 212\u2013220 (2017)","DOI":"10.1109\/CVPR.2017.713"},{"key":"74_CR9","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: CosFace: large margin cosine loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5265\u20135274 (2018)","DOI":"10.1109\/CVPR.2018.00552"},{"key":"74_CR10","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Xue, N., Zafeiriou, S.: ArcFace: additive angular margin loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4690\u20134699 (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"key":"74_CR11","doi-asserted-by":"crossref","unstructured":"Huang, Y., et al.: CurricularFace: adaptive curriculum learning loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5901\u20135910 (2020)","DOI":"10.1109\/CVPR42600.2020.00594"},{"key":"74_CR12","unstructured":"Zeng, D., Shi, H., Du, H., Wang, J., Lei, Z., Mei, T.: NPCFace: a negative-positive cooperation supervision for training large-scale face recognition. arXiv preprint arXiv:2007.10172 (2020)"},{"key":"74_CR13","doi-asserted-by":"crossref","unstructured":"Wang, X., Zhang, S., Wang, S., Fu, T., Shi, H. and Mei, T.: Mis-classified vector guided Softmax loss for face recognition. Association for the Advancement of Artificial Intelligence (AAAI), New York, USA (2020)","DOI":"10.1609\/aaai.v34i07.6906"},{"key":"74_CR14","doi-asserted-by":"crossref","unstructured":"Zhang, X., Fang, Z., Wen, Y., Li, Z. and Qiao, Y.: Range loss for deep face recognition with long-tailed training data. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5409\u20135418 (2017)","DOI":"10.1109\/ICCV.2017.578"},{"key":"74_CR15","doi-asserted-by":"crossref","unstructured":"Liu, H., Zhu, X., Lei, Z., Li, S.Z.: AdaptiveFace: adaptive margin and sampling for face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 11947\u201311956 (2019)","DOI":"10.1109\/CVPR.2019.01222"},{"key":"74_CR16","doi-asserted-by":"publisher","first-page":"107012","DOI":"10.1016\/j.patcog.2019.107012","volume":"97","author":"X Wei","year":"2020","unstructured":"Wei, X., Wang, H., Scotney, B., Wan, H.: Minimum margin loss for deep face recognition. Pattern Recogn. 97, 107012 (2020)","journal-title":"Pattern Recogn."}],"container-title":["Lecture Notes in Electrical Engineering","Proceedings of the 11th International Conference on Robotics, Vision, Signal Processing and Power Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-8129-5_74","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T19:33:38Z","timestamp":1648582418000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-8129-5_74"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811681288","9789811681295"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-8129-5_74","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"11 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}