[1] NAM H,HAN B.Learning multi-domain convolutional neural networks for visual tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:4293-4302. [2] TAO R,GAVVES E,SMEULDERS A W M.Siamese instance search for tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:1420-1429. [3] DANELLJAN M,HAGER G,SHAHBAZ KHAN F,et al.Convolutional features for correlation filter based visual tracking[C]//Proceedings of IEEE International Conference on Computer Vision Workshops.Washington D.C.,USA:IEEE Press,2015:58-66. [4] DANELLJAN M,BHAT G,SHAHBAZ KHAN F,et al.ECO:efficient convolution operators for tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:6638-6646. [5] WANG L,OUYANG W,WANG X,et al.STCT:sequentially training convolutional networks for visual tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:1373-1381. [6] CHATFIELD K,SIMONYAN K,VEDALDI A,et al.Return of the devil in the details:delving deep into convolutional nets[EB/OL].[2020-02-05].http://de.arxiv.org/pdf/1405.3531. [7] SAITO K,WATANABE K,USHIKU Y,et al.Maximum classifier discrepancy for unsupervised domain adaptation[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2018:3723-3732. [8] YAN X,YANG J,SOHN K,et al.Attribute2Image:conditional image generation from visual attributes[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2016:776-791. [9] DU B,XIONG W,WU J,et al.Stacked convolutional denoising auto-encoders for feature representation[J].IEEE Transactions on Cybernetics,2016,47(4):1017-1027. [10] RUSSAKOVSKY O,DENG J,SU H,et al.Imagenet large scale visual recognition challenge[J].International Journal of Computer Vision,2015,115(3):211-252. [11] HENRIQUES J F,CASEIRO R,MARTINS P,et al.High-speed tracking with kernelized correlation filters[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,37(3):583-596. [12] LI Y,ZHU J.A scale adaptive kernel correlation filter tracker with feature integration[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2014:254-265. [13] DANELLJAN M,HÄGER G,KHAN F,et al.Accurate scale estimation for robust visual tracking[C]//Proceedings of British Machine Vision Conference.Washington D.C.,USA:IEEE Press,2014:15-22. [14] ZHANG K,ZHANG L,LIU Q,et al.Fast visual tracking via dense spatio-temporal context learning[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2014:127-141. [15] MA C,HUANG J B,YANG X,et al.Hierarchical convolutional features for visual tracking[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:3074-3082. [16] DANELLJAN M,HAGER G,SHAHBAZ KHAN F,et al.Learning spatially regularized correlation filters for visual tracking[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:4310-4318. [17] WANG N,LI S,GUPTA A,et al.Transferring rich feature hierarchies for robust visual tracking[EB/OL].[2020-02-05].https://arxiv.org/pdf/1501.04587.pdf. [18] NAM H,HAN B.Learning multi-domain convolutional neural networks for visual tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:4293-4302. [19] WANG L,OUYANG W,WANG X,et al.Visual tracking with fully convolutional networks[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:3119-3127. [20] FAN H,LING H.SANet:structure-aware network for visual tracking[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops.Washington D.C.,USA:IEEE Press,2017:42-49. [21] YUN S,CHOI J,YOO Y,et al.Action-decision networks for visual tracking with deep reinforcement learning[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:2711-2720. [22] BEN-DAVID S,BLITZER J,CRAMMER K,et al.A theory of learning from different domains[J].Machine Learning,2010,79(1/2):151-175. [23] GOODFELLOW I,POUGET-ABADIE J,MIRZA M,et al.Generative adversarial nets[EB/OL].[2020-02-05].https://papers.nips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf. [24] KINGMA D P,BA J.Adam:a method for stochastic optimization[EB/OL].[2020-02-05].http://de.arxiv.org/pdf/1412.6980. [25] WU Y,LIM J,YANG M H.Object tracking benchmark[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2015,37(9):1834-1848. [26] CHOI J,JIN CHANG H,JEONG J,et al.Visual tracking using attention-modulated disintegration and integration[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:4321-4330. [27] BERTINETTO L,VALMADRE J,HENRIQUES J F,et al.Fully-convolutional siamese networks for object tracking[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2016:850-865. [28] MAATEN L,HINTON G.Visualizing data using t-SNE[J].Journal of Machine Learning Research,2008,9:2579-2605. |