{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:18:07Z","timestamp":1750220287158,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T00:00:00Z","timestamp":1645142400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,2,18]]},"DOI":"10.1145\/3529836.3529839","type":"proceedings-article","created":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T20:27:55Z","timestamp":1655843275000},"page":"519-525","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Lucas-Kanade-based Face Detection Network: An Unsupervised Approach to Improve the Precision and Stability of video-based Face Detector"],"prefix":"10.1145","author":[{"given":"Changyan","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Zhongshan Institute,University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Zhongshan Institute,University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wensheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Zhongshan Institute,University of Electronic Science and Technology of China, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,6,21]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2010.5537907"},{"key":"e_1_3_2_1_2_1","unstructured":"Krizhevsky A Sutskever I Hinton G E. 2012. Convolutional networks and applications in vision. J. Advances in neural information processing systems 25:1097-1105.  Krizhevsky A Sutskever I Hinton G E. 2012. Convolutional networks and applications in vision. J. Advances in neural information processing systems 25:1097-1105."},{"volume-title":"Deep learning","author":"Goodfellow I","key":"e_1_3_2_1_3_1","unstructured":"Goodfellow I , Bengio Y , Courville A , 2016. Deep learning . Cambridge : MIT press . Goodfellow I, Bengio Y, Courville A, 2016. Deep learning. Cambridge: MIT press."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"e_1_3_2_1_5_1","unstructured":"Simonyan K Zisserman A. 2014. Very deep convolutional networks for large-scale image recognition. J. arXiv preprint arXiv:1409.1556.  Simonyan K Zisserman A. 2014. Very deep convolutional networks for large-scale image recognition. J. arXiv preprint arXiv:1409.1556."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"volume-title":"Region-Based Convolutional Networks for Accurate Object Detection and Segmentation","author":"Girshick R","key":"e_1_3_2_1_7_1","unstructured":"Girshick R , Donahue J , Darrell T , 2015. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation . J. IEEE Transactions on Pattern Analysis & Machine Intelligence . 38(1):142-158. Girshick R, Donahue J, Darrell T, 2015. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation. J. IEEE Transactions on Pattern Analysis & Machine Intelligence. 38(1):142-158."},{"volume-title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","author":"Ren S","key":"e_1_3_2_1_8_1","unstructured":"Ren S , He K , Girshick R , 2017. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks . J. IEEE Transactions on Pattern Analysis & Machine Intelligence . 39(6):1137-1149. Ren S, He K, Girshick R, 2017. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. J. IEEE Transactions on Pattern Analysis & Machine Intelligence. 39(6):1137-1149."},{"key":"e_1_3_2_1_9_1","volume-title":"Mask RCNN. In Proceedings of the IEEE international conference on computer vision. IEEE, 2961-2969","author":"He K","year":"2017","unstructured":"He K , Gkioxari G , Doll\u00e1r P , 2017 . Mask RCNN. In Proceedings of the IEEE international conference on computer vision. IEEE, 2961-2969 . He K, Gkioxari G, Doll\u00e1r P, 2017. Mask RCNN. In Proceedings of the IEEE international conference on computer vision. IEEE, 2961-2969."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"e_1_3_2_1_11_1","unstructured":"Redmon J Farhadi A. 2018. Yolov3: An incremental improvement. J. arXiv preprint arXiv:1804.02767.  Redmon J Farhadi A. 2018. Yolov3: An incremental improvement. J. arXiv preprint arXiv:1804.02767."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.690"},{"key":"e_1_3_2_1_13_1","volume-title":"Liao H Y M","author":"Bochkovskiy A","year":"2020","unstructured":"Bochkovskiy A , Wang C Y , Liao H Y M . 2020 . Yolov4: Optimal speed and accuracy of object detection. J. arXiv preprint arXiv:2004.10934. Bochkovskiy A, Wang C Y, Liao H Y M. 2020. Yolov4: Optimal speed and accuracy of object detection. J. arXiv preprint arXiv:2004.10934."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_45"},{"key":"e_1_3_2_1_17_1","volume-title":"Objects as facial landmarks. J. arXiv preprint arXiv:1904.07850","author":"Zhou X","year":"2019","unstructured":"Zhou X , Wang D , Kr\u00e4henb\u00fchl P. 2019. Objects as facial landmarks. J. arXiv preprint arXiv:1904.07850 , 2019 . Zhou X, Wang D, Kr\u00e4henb\u00fchl P. 2019. Objects as facial landmarks. J. arXiv preprint arXiv:1904.07850, 2019."},{"key":"e_1_3_2_1_18_1","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision. IEEE","author":"Duan K","year":"2019","unstructured":"Duan K , Bai S , Xie L , 2019 . Centernet: Keyfacial landmark triplets for object detection . In Proceedings of the IEEE\/CVF International Conference on Computer Vision. IEEE , 2019: 6569-6578. Duan K, Bai S, Xie L, 2019. Centernet: Keyfacial landmark triplets for object detection. In Proceedings of the IEEE\/CVF International Conference on Computer Vision. IEEE, 2019: 6569-6578."},{"key":"e_1_3_2_1_19_1","volume-title":"Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641.","author":"Deng J","year":"2019","unstructured":"Deng J , Guo J , Zhou Y , 2019 . Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641. Deng J, Guo J, Zhou Y, 2019. Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641."},{"volume-title":"Proceedings of European Conference on Computer Vision (ECCV)","year":"2018","key":"e_1_3_2_1_20_1","unstructured":"TANG X, DU D K, HE Z , 2018 . Pyramidbox: A Context - Assisted Single Shot Face Detector . In Proceedings of European Conference on Computer Vision (ECCV) . Munich,Germany , 2018: 797-813. DOI: 10.1007\/978-3-030-01240-3_49. 10.1007\/978-3-030-01240-3_49 TANG X, DU D K, HE Z, 2018. Pyramidbox: A Context - Assisted Single Shot Face Detector. In Proceedings of European Conference on Computer Vision (ECCV). Munich,Germany, 2018: 797-813. DOI: 10.1007\/978-3-030-01240-3_49."},{"volume-title":"Proceedings of IEEE International Conference on Computer Vision","year":"2017","key":"e_1_3_2_1_21_1","unstructured":"ZHANG S, ZHU X, LEI Z , 2017 . S3FD: Single Shot Scale-Invariant Face Detector . In Proceedings of IEEE International Conference on Computer Vision . Venice, Italy ,2017: 192-201. DOI: 10.1109\/ICCV.2017.30. 10.1109\/ICCV.2017.30 ZHANG S, ZHU X, LEI Z, 2017. S3FD: Single Shot Scale-Invariant Face Detector. In Proceedings of IEEE International Conference on Computer Vision. Venice, Italy,2017: 192-201. DOI: 10.1109\/ICCV.2017.30."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00045"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.202"},{"key":"e_1_3_2_1_24_1","volume-title":"Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641","author":"Deng J","year":"2019","unstructured":"Deng J , Guo J , Zhou Y , 2019 . Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641 , 2019. Deng J, Guo J, Zhou Y, 2019. Retinaface: Single-stage dense face localisation in the wild. J. arXiv preprint arXiv:1905.00641, 2019."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.596"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_26"},{"key":"e_1_3_2_1_27_1","volume-title":"Learning characteristics of stochastic-gradient-descent algorithms: A general study, analysis, and critique. J. Signal processing","author":"Gardner W A","year":"1984","unstructured":"Gardner W A . 1984. Learning characteristics of stochastic-gradient-descent algorithms: A general study, analysis, and critique. J. Signal processing , 1984 , 6(2): 113-133. Gardner W A. 1984. Learning characteristics of stochastic-gradient-descent algorithms: A general study, analysis, and critique. J. Signal processing, 1984, 6(2): 113-133."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/NNSP.1992.253713"},{"key":"e_1_3_2_1_29_1","volume-title":"Adam: A method for stochastic optimization. J. arXiv preprint arXiv:1412.6980","author":"Kingma D P","year":"2014","unstructured":"Kingma D P , Ba J. 2014 . Adam: A method for stochastic optimization. J. arXiv preprint arXiv:1412.6980 , 2014. Kingma D P, Ba J. 2014. Adam: A method for stochastic optimization. J. arXiv preprint arXiv:1412.6980, 2014."},{"key":"e_1_3_2_1_30_1","unstructured":"Dozat T. 2016. Incorporating nesterov momentum into adam. J. ICLR 2016.  Dozat T. 2016. Incorporating nesterov momentum into adam. J. ICLR 2016."},{"key":"e_1_3_2_1_31_1","volume-title":"Adaptive subgradient methods for online learning and stochastic optimization. J. Journal of machine learning research","author":"Duchi J","year":"2011","unstructured":"Duchi J , Hazan E , Singer Y. 2011. Adaptive subgradient methods for online learning and stochastic optimization. J. Journal of machine learning research , 2011 , 12(7). Duchi J, Hazan E, Singer Y. 2011. Adaptive subgradient methods for online learning and stochastic optimization. J. Journal of machine learning research, 2011, 12(7)."},{"key":"e_1_3_2_1_32_1","volume-title":"Stochastic gradient descent tricks\/\/Neural networks: Tricks of the trade","author":"Bottou L.","year":"2012","unstructured":"Bottou L. 2012. Stochastic gradient descent tricks\/\/Neural networks: Tricks of the trade . Springer , Berlin, Heidelberg , 2012 : 421-436. Bottou L. 2012. Stochastic gradient descent tricks\/\/Neural networks: Tricks of the trade. Springer, Berlin, Heidelberg, 2012: 421-436."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.9.1.20-26"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.4.1.1-5"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.18178\/joig.4.1.15-19"},{"key":"e_1_3_2_1_36_1","volume-title":"NIPS","author":"Ren K.","year":"2015","unstructured":"S. Ren , K. He , R. Girshick , and J. Sun . Faster R-CNN: Towards realtime object detection with region proposal networks . In NIPS , 2015 . 1, 8, 9, 12 S. Ren, K. He, R. Girshick, and J. Sun. Faster R-CNN: Towards realtime object detection with region proposal networks. In NIPS, 2015. 1, 8, 9, 12"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"Shifeng Zhang Xiangyu Zhu 2017.S 3FD: Single Shot Scale-invariant Face Detector. In ICCV arXiv:1708.05237.  Shifeng Zhang Xiangyu Zhu 2017.S 3FD: Single Shot Scale-invariant Face Detector. In ICCV arXiv:1708.05237.","DOI":"10.1109\/ICCV.2017.30"},{"key":"e_1_3_2_1_38_1","volume-title":"ICPR","author":"Ohn-Bar M. M.","year":"2017","unstructured":"E. Ohn-Bar and M. M. Trivedi . To Boost or not to Boost: On the Limits of Boosted Neural Networks . In ICPR , 2017 . 7, 8 E. Ohn-Bar and M. M. Trivedi. To Boost or not to Boost: On the Limits of Boosted Neural Networks. In ICPR, 2017. 7, 8"},{"key":"e_1_3_2_1_39_1","first-page":"7","author":"Zhang Z.","year":"2016","unstructured":"K. Zhang , Z. Zhang , Z. Li , and Y. Qiao . Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters , 2016 . 7 , 8. K. Zhang, Z. Zhang, Z. Li, and Y. Qiao. Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters, 2016. 7, 8.","journal-title":"IEEE Signal Processing Letters"},{"key":"e_1_3_2_1_40_1","unstructured":"C. Zhu Y. Zheng K. Luu and M. Savvides. 2016.Cms-rcnn: contextual multi-scale region-based cnn for unconstrained face detection. arXiv preprint arXiv:1606.05413 2016. 7 8.  C. Zhu Y. Zheng K. Luu and M. Savvides. 2016.Cms-rcnn: contextual multi-scale region-based cnn for unconstrained face detection. arXiv preprint arXiv:1606.05413 2016. 7 8."},{"key":"e_1_3_2_1_41_1","volume-title":"Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua","author":"Hu P.","year":"2017","unstructured":"Hu , P. and Ramanan , D . 2017. Finding tiny faces . Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua , ( 2017 ), 1522\u20131530. Hu, P. and Ramanan, D. 2017. Finding tiny faces. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua, (2017), 1522\u20131530."},{"key":"e_1_3_2_1_42_1","volume-title":"Face Detection through Scale-Friendly Deep Convolutional Networks. arXiv:1706.02863v1 [cs.CV]","author":"Shuo Yang","year":"2017","unstructured":"Shuo Yang , Yuanjun Xiong 2017. Face Detection through Scale-Friendly Deep Convolutional Networks. arXiv:1706.02863v1 [cs.CV] 9 Jun 2017 . Shuo Yang, Yuanjun Xiong 2017. Face Detection through Scale-Friendly Deep Convolutional Networks. arXiv:1706.02863v1 [cs.CV] 9 Jun 2017."}],"event":{"name":"ICMLC 2022: 2022 14th International Conference on Machine Learning and Computing","acronym":"ICMLC 2022","location":"Guangzhou China"},"container-title":["2022 14th International Conference on Machine Learning and Computing (ICMLC)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529836.3529839","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3529836.3529839","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:31:25Z","timestamp":1750188685000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3529836.3529839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,18]]},"references-count":42,"alternative-id":["10.1145\/3529836.3529839","10.1145\/3529836"],"URL":"https:\/\/doi.org\/10.1145\/3529836.3529839","relation":{},"subject":[],"published":{"date-parts":[[2022,2,18]]},"assertion":[{"value":"2022-06-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}