乾貨 | 美團如何基於深度學習實現影象的智慧稽核？
阿新 • • 發佈：2019-01-06
[1]H. Chen, S. S. Tsai, G. Schroth, D. M. Chen, R. Grzeszczuk, and B. Girod. “Robust text detection in natural images with edge-enhanced maximally stable extremal regions.” ICIP 2011.
[2]Z Zhong,LJin,SZhang,ZFeng.“DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images”. Architecture Science 2015.
[3]Minghui Liao, Baoguang Shi, Xiang Bai, Xinggang Wang, Wenyu Liu. “TextBoxes: A Fast Text Detector with a Single Deep Neural Network”. AAAI 2017.
[4]S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn.“Towards real-time object detection with region proposal networks.” NIPS 2015.
[5]Graves, A.; Fernandez, S.; Gomez, F.; and Schmidhuber, J. “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks.” ICML 2006.
[6]R Girshick,JDonahue,TDarrell,JMalik. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” CVPR 2014.
[7]J. Redmon, S. Divvala, R. Girshick, and A. Farhadi. “You only look once: Unified, real-time object detection”. CVPR 2016.
[8]W. Liu, D. Anguelov, D. Erhan, C. Szegedy, and S. Reed. “SSD: Single shot multibox detector”. ECCV 2016.
[9] “Object detection with discriminatively trained part-based models”. TPAMI 2010.
[10]Robust Real-time Object Detection. Paul Viola, Michael Jones. IJCV 2004.
[11]N. Markus, M. Frljak, I. S. Pandzic, J. Ahlberg and R. Forchheimer. “Object Detection with Pixel Intensity Comparisons Organized in Decision Trees”. CoRR 2014.
[12]Shengcai Liao, Anil K. Jain, and Stan Z. Li. “A Fast and Accurate Unconstrained Face Detector,” TPAMI 2015.
[13]Dong Chen, ShaoQingRen, Jian Sun. “Joint Cascade Face Detection and Alignment”, ECCV 2014.
[14]Haoxiang Li, Zhe Lin, XiaohuiShen, Jonathan Brandt, Gang Hua. “A convolutional neural network cascade for face detection”, CVPR.2015.
[15]Lichao Huang, Yi Yang, Yafeng Deng, Yinan Yu.“DenseBox: Unifying Landmark Localization with End to End Object Detection” CVPR 2015.
[16]Taigman Y, Yang M, Ranzato M A, et al. Deepface: Closing the gap to human-level performance in face verification.CVPR 2014.
[17]Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes.CVPR 2014.
[18]Sun Y, Chen Y, Wang X, et al. Deep learning face representation by joint identification-verification.NIPS. 2014.
[19]FaceNet: A Unified Embedding for Face Recognition and Clustering. CVPR 2015.
[20]A Discriminative Feature Learning Approach for Deep Face Recognition. ECCV 2016.
[21]Rethinking the Inception Architecture for Computer Vision. CVPR 2016.
[22]Alex Krizhevsky, IlyaSutskever, Geoffrey E. Hinton. “ImageNet Classification with Deep Convolutional Neural Networks”. 2014.
[23]Murray, N., Marchesotti, L., Perronnin, F. “Ava: A large-scale database for aesthetic visual analysis”. CVPR 2012.
[2]Z Zhong,LJin,SZhang,ZFeng.“DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images”. Architecture Science 2015.
[3]Minghui Liao, Baoguang Shi, Xiang Bai, Xinggang Wang, Wenyu Liu. “TextBoxes: A Fast Text Detector with a Single Deep Neural Network”. AAAI 2017.
[4]S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn.“Towards real-time object detection with region proposal networks.” NIPS 2015.
[5]Graves, A.; Fernandez, S.; Gomez, F.; and Schmidhuber, J. “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks.” ICML 2006.
[6]R Girshick,JDonahue,TDarrell,JMalik. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” CVPR 2014.
[7]J. Redmon, S. Divvala, R. Girshick, and A. Farhadi. “You only look once: Unified, real-time object detection”. CVPR 2016.
[8]W. Liu, D. Anguelov, D. Erhan, C. Szegedy, and S. Reed. “SSD: Single shot multibox detector”. ECCV 2016.
[9] “Object detection with discriminatively trained part-based models”. TPAMI 2010.
[10]Robust Real-time Object Detection. Paul Viola, Michael Jones. IJCV 2004.
[11]N. Markus, M. Frljak, I. S. Pandzic, J. Ahlberg and R. Forchheimer. “Object Detection with Pixel Intensity Comparisons Organized in Decision Trees”. CoRR 2014.
[12]Shengcai Liao, Anil K. Jain, and Stan Z. Li. “A Fast and Accurate Unconstrained Face Detector,” TPAMI 2015.
[13]Dong Chen, ShaoQingRen, Jian Sun. “Joint Cascade Face Detection and Alignment”, ECCV 2014.
[14]Haoxiang Li, Zhe Lin, XiaohuiShen, Jonathan Brandt, Gang Hua. “A convolutional neural network cascade for face detection”, CVPR.2015.
[15]Lichao Huang, Yi Yang, Yafeng Deng, Yinan Yu.“DenseBox: Unifying Landmark Localization with End to End Object Detection” CVPR 2015.
[16]Taigman Y, Yang M, Ranzato M A, et al. Deepface: Closing the gap to human-level performance in face verification.CVPR 2014.
[17]Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10,000 classes.CVPR 2014.
[18]Sun Y, Chen Y, Wang X, et al. Deep learning face representation by joint identification-verification.NIPS. 2014.
[19]FaceNet: A Unified Embedding for Face Recognition and Clustering. CVPR 2015.
[20]A Discriminative Feature Learning Approach for Deep Face Recognition. ECCV 2016.
[21]Rethinking the Inception Architecture for Computer Vision. CVPR 2016.
[22]Alex Krizhevsky, IlyaSutskever, Geoffrey E. Hinton. “ImageNet Classification with Deep Convolutional Neural Networks”. 2014.
[23]Murray, N., Marchesotti, L., Perronnin, F. “Ava: A large-scale database for aesthetic visual analysis”. CVPR 2012.