박사

변분적 오토인코더와 외부 메모리를 이용한 실시간 객체추적

박근호 2019년
논문상세정보
' 변분적 오토인코더와 외부 메모리를 이용한 실시간 객체추적' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Deep learning
  • Siamese nerwork
  • external memory
  • object tracking
  • variational auto-encoder
  • 객체 추적
  • 딥 러닝
  • 변분적 오토인코더
  • 샴 네트워크
  • 외부 메모리
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
3,295 0

0.0%

' 변분적 오토인코더와 외부 메모리를 이용한 실시간 객체추적' 의 참고문헌

  • Z. Hong, Z. Chen, C. Wang, X. Mei, D. Prokhorov and D. Tao , "MUlti Store Tracker (MUSTer): A cognitive psy chology inspired approach to object tracking," in 2015 IEEE Conference on Computer Vision and Pattern Recogni tion , Boston, MA, 2015.
  • Y. Wu, J. Lim and M. Yang, "Online Object Tracking: A Benchmark," in Benchmark," in IEEE ConferenIEEE Conference on Computter Vision and ce on Computter Vision and Pattern RecognitionPattern Recognition, Portland, OR, 2013. , Portland, OR, 2013.
  • Y. Wu, J. Lim and M. Yang, "Object Tracking Benchmark," IEEE Transactions on Pattern Analysis and Machine IntelIEEE Transactions on Pattern Analysis and Machine Intel--ligence, ligence, vol. 37, no. 9, pp. 1834vol. 37, no. 9, pp. 1834--1848, Sep. 2015. 1848, Sep. 2015.
  • Y. Wu, B. Shen and H. Ling, "Online robust image align--ment via iterative convex optimization," in ment via iterative convex optimization," in 2012 IEEE Con2012 IEEE Con--ference on Coference on Computer Vision and Pattern Recognitionmputer Vision and Pattern Recognition, Prov, Prov--idence, RI, 2012. idence, RI, 2012.
  • Y. Song, C. Ma, X. Wu, L. Gong, L. Bao, W. Zuo, C. Shen, R. R. W. H. Lau and M. Yang, "VITAL: VIsual tracking via adW. H. Lau and M. Yang, "VITAL: VIsual tracking via ad--versarial learning," versarial learning," 2018 IEEE/CVF Conference on Com2018 IEEE/CVF Conference on Com--puter Vision and Pattern Recognition, puter Vision and Pattern Recognition, pp. 8990pp. 8990--8999, 8999, 2018. 2018.
  • Y. Qi, S. Zhang, L. Qin, H. Yao, Q. Huang, J. Lim and M. H. H. Yang, "Hedged Deep Tracking," in Yang, "Hedged Deep Tracking," in 2016 IEEE Conference 2016 IEEE Conference on Computer Vision and Pattern Recoon Computer Vision and Pattern Recognitiongnition, Las Vegas, , Las Vegas, NV, 2016. NV, 2016.
  • Y. Li and J. Zhu, "A scale adaptive kernel correlation filter tracker with feature integration," i n ECCV Workshops , 2014.
  • Y. LeCun, L. Bottou, Y. Bengio and P. Haffner, "Gradient--based learning applied to document recognibased learning applied to document recognition," vol. 86, tion," vol. 86, no. 11, pp. 2278no. 11, pp. 2278--2324, 1998. 2324, 1998.
  • Y. Bengio, P. Lamblin, D. Popovici and H. Larochelle, "Greedy Layer"Greedy Layer--wise Training of Deep Networks," in wise Training of Deep Networks," in ProPro--cceedings of the 19th International Conference on Neural eedings of the 19th International Conference on Neural Information Processing SystemsInformation Processing Systems, MIT Press, 2006, pp. , MIT Press, 2006, pp. 153153--160.160.
  • X. Guo, X. Liu, E. Zhu and J. Yin, "Deep Clustering with Convolutional Autoencoders," in Convolutional Autoencoders," in International Conference International Conference on Neural Informaton Neural Information Processingion Processing, 2017. , 2017.
  • T. Zhang, C. Xu and M. Yang, "MultiC. Xu and M. Yang, "Multi--task Correlation Partitask Correlation Parti--cle Filter for Robust Object Tracking," in cle Filter for Robust Object Tracking," in 2017 IEEE Con2017 IEEE Con--ference on Computer Vision and Pattern Recognitionference on Computer Vision and Pattern Recognition, Hon, Hon--olulu, HI, 2017. olulu, HI, 2017.
  • T. Zhang, B. Ghanem, S. Liu and N. Ahuja, "Robust visual tracking viatracking via multimulti--task sparse learning," in task sparse learning," in 2012 IEEE Con2012 IEEE Con--ference on Computer Vision and Pattern Recognitionference on Computer Vision and Pattern Recognition, Prov, Prov--idence, RI, 2012. idence, RI, 2012.
  • S. Yun, J. Choi, Y. Yoo, K. Yun and J. Y. Choi, "Actionn and J. Y. Choi, "Action--decideci--sion networks for visual tracking with deep reinforcement sion networks for visual tracking with deep reinforcement learning," in learning," in 2017 IEEE Conference on Computer Vision 2017 IEEE Conference on Computer Vision and Pattern Recognitionand Pattern Recognition, Honolulu, HI, 2017. , Honolulu, HI, 2017.
  • P. Vincent, H. Larochelle, Y. Bengio and P. Manzagol, "Ex--tracting and Composing Robust Features with Denoising tracting and Composing Robust Features with Denoising AutoencAutoencoders," in oders," in Proceedings of the 25th International Proceedings of the 25th International Conference on Machine LearningConference on Machine Learning, Helsinki, ACM, 2008, pp. , Helsinki, ACM, 2008, pp. 10961096--1103.1103.
  • M. Mueller, N. Smith and B. Ghanem, "Context aware cor relation filter tracking," in 2017 IEEE Conference on Com puter Vision and Pattern Recognition , Honolulu, HI, 2017.
  • M. Kristan, "The Visual Object Tracking VOT2017 Chal--lenge Results," in lenge Results," in 2017 IEEE International Conference on 2017 IEEE International Conference on Computer Vision WorkshopsComputer Vision Workshops, Venice, 2017. , Venice, 2017.
  • M. Kristan, "The Visual Object Tracking VOT2016 Chal--lenge Results," in lenge Results," in ECCV 2016 WorkshopsECCV 2016 Workshops, 2016. , 2016.
  • M. Kristan, "The Visual Object Tracking VOT2015 Chaln, "The Visual Object Tracking VOT2015 Chal--lenge Results," in lenge Results," in 2015 IEEE International Conference on 2015 IEEE International Conference on Computer Vision WorkshopComputer Vision Workshop, Santiago, 2015. , Santiago, 2015.
  • M. Danelljan, G. Hager, F. Khan and M. Felsberg, "Discrim--inative Scaleinative Scale Space Tracking," Space Tracking," IEEE Transactions on PatIEEE Transactions on Pat--tern Analysis and Machine Intelligence, tern Analysis and Machine Intelligence, pp. 1pp. 1--14, 2017. 14, 2017.
  • M. Danelljan, G. Bhat, F. S. Khan and M. Felsberg, "ECO: Efficient convolution operators for tracking," Efficient convolution operators for tracking," 2017 IEEE 2017 IEEE Conference on Computer Vision and Pattern Recognition, Conference on Computer Vision and Pattern Recognition, pp. 6931pp. 6931--6939, 2017. 6939, 2017.
  • M. Danelljan, A. Robinson, F. S. Khan and M. Felsberg, "Beyond Cor relation Filters: Learning continuous convolu tion operators for visual tracking," in ECCV , 2016.
  • M. D. Zeiler and R. Fergus, "Visualizing and Understanding Convolutional Networks," in Convolutional Networks," in ECCV 2014ECCV 2014, 2014. , 2014.
  • M. A. Ranzato, Y. Boureau and Y. LeCun, "Sparse Feature Learning for Deep Belief Networks," in Learning for Deep Belief Networks," in Proceedings of the Proceedings of the 20th International20th International Conference on Neural Information ProcConference on Neural Information Proc-- essing Systems, Vancouver, British Columbia, Curran As, Vancouver, British Columbia, Curran As--sociates Inc., 2007, pp. 1185sociates Inc., 2007, pp. 1185--1192.1192.
  • L. Sevilla--Lara, "Distribution Fields for Tracking," in Lara, "Distribution Fields for Tracking," in ProPro--ceedings of the2012 IEEE Conference on Computer Vision ceedings of the2012 IEEE Conference on Computer Vision and Pattern Recognitionand Pattern Recognition, Washington, DC, USA, 2012. , Washington, DC, USA, 2012.
  • L. Bertinetto, J. Valmadre, J. F. Henriques, A. Vedaldi and P. H. S. Torr, "FullyP. H. S. Torr, "Fully--convolutional Siamese convolutional Siamese networks for networks for object," in object," in ECCV workshopECCV workshop, 2016. , 2016.
  • K. Zhang, L. Zhang and M. Yang, "Real--time Compressive time Compressive Tracking," in Tracking," in Proceedings of the 12th European ConferProceedings of the 12th European Confer--ence on Computer Visionence on Computer Vision, Florence, Italy, 2012, Florence, Italy, 2012. .
  • K. Simonyan and A. Zisserman, "Very Deep Convolutional Networks for LargeNetworks for Large--Scale Image Recognition," Scale Image Recognition," CoRR, CoRR, 2015. 2015.
  • K. He, X. Zhang, S. Ren and J. Sun, "Deep Residual Learn--ing for Image Recognition," ing for Image Recognition," 2016 IEEE Conference on 2016 IEEE Conference on Computer Vision and Pattern Recognition, Computer Vision and Pattern Recognition, pp. 770pp. 770--778, 778, 2016. 2016.
  • J. Valmadre, L. Bertinetto, J. Henriques, A. Vedaldi and P. H. S. Torr, "EndH. S. Torr, "End--toto--end representation learning for correlaend representation learning for correla--tion filter based tracking," in tion filter based tracking," in CVPRCVPR, 2017. , 2017.
  • J. F. Henriques, R. Caseiro, P. Martins and J. Batista, "High speed tracking with kernelized correlation filters," IEEE Transactions on Pattern Analysis and Machine Intel ligence, vol. 37, p. 583 596, 2015.
  • J. F. Henriques, R. Caseiro, P. Martins and J. Batista, "Ex--ploiting the Circulant Structure of Trackingploiting the Circulant Structure of Tracking--byby--Detection Detection with Kernels,with Kernels," in " in Proceedings of the 12th European ConProceedings of the 12th European Con--ference on Computer Visionference on Computer Vision, Florence, Italy, 2012. , Florence, Italy, 2012.
  • J. Choi, H. J. Chang, J. Jeong, Y. Demiris and J. Y. Choi, , J. Jeong, Y. Demiris and J. Y. Choi, "Visual Tracking Using Attention"Visual Tracking Using Attention--Modulated Disintegration Modulated Disintegration and Integration," in and Integration," in 2016 IEEE Conference on Computer 2016 IEEE Conference on Computer Vision and Pattern RecognitionVision and Pattern Recognition, Las Vegas, NV, 2016. , Las Vegas, NV, 2016.
  • H. Nam and B. Han, "Learning multi--domain convolutional domain convolutional neural networks for visual tracking," in neural networks for visual tracking," in CVPRCVPR, 2016. , 2016.
  • H. Fan and H. Ling, "SANet: Structure--Aware Network for Aware Network for Visual Tracking," in Visual Tracking," in 2017 IEEE Conference on Computer 2017 IEEE Conference on Computer Vision and Pattern Recognition WorkshopsVision and Pattern Recognition Workshops, 2017. , 2017.
  • G. Huang, Z. Liu, L. V. D. Maaten and K. Q. Weinberger, "Densely Connect"Densely Connected Convolutional Networks," in ed Convolutional Networks," in 2017 2017 IEEE Conference on Computer Vision and Pattern RecogniIEEE Conference on Computer Vision and Pattern Recogni--tiontion, Honolulu, HI, 2017. , Honolulu, HI, 2017.
  • F. Li, C. Tian, W. Zuo, L. Zhang and M. H. Yang, "Learning and M. H. Yang, "Learning spatialspatial--temporal regularized correlation filters for visual temporal regularized correlation filters for visual tracking," in tracking," in CVPRCVPR, 2018. , 2018.
  • D. S. Bolme, J. R. Beveridge, B. A. Draper and Y. M. Lui, "Visual object tracking using adaptive correlation filters," in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition , San Francisco, CA, 2010.
  • D. P. Kingma and M. Welling, "Auto--encoding variational encoding variational bayes," in bayes," in Proceedings of the InternatiProceedings of the International Conference on onal Conference on Learning RepresentationsLearning Representations, 2014. , 2014.
  • C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke and AAnguelov, D. Erhan, V. Vanhoucke and A. Rabinovich, "Go. Rabinovich, "Go--ing deeper with convolutions," in ing deeper with convolutions," in 2015 IEEE Conference 2015 IEEE Conference on Computer Vision and Pattern Recognitionon Computer Vision and Pattern Recognition, Boston, MA, , Boston, MA, 2015. 2015.
  • C. Ma, X. Yang, C. Zhang and M. Yang, "Long term correla tion tracking," in 2015 IEEE Conference on Computer Vi sion and Pattern Recognition , Boston, MA, 2015.
  • C. Ma, X. Huang and M. Yang, "Hierarchical convolutional features for visual tracking," in features for visual tracking," in 2015 IEEE International 2015 IEEE International Conference on ComputConference on Computer Visioner Vision, Santiago, 2015. , Santiago, 2015.
  • C. Bao, Y. Wu, H. Ling and H. Ji, "Real time robust L1 tracker using accelerated proximal gradient approach," in tracker using accelerated proximal gradient approach," in 2012 IEEE Conference on Computer Vision and Pattern 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 2012. , Providence, RI, 2012.
  • A. Krizhevsky, I. Sutskever and G. E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks," Classification with Deep Convolutional Neural Networks," 2012. 2012.
  • A. Graves, G. Wayne and I. Danihelka, "Neural turing ma--chines," in chines," in CoRRCoRR, 2014. , 2014.