Explorer Action Recognition with Dynamic Image Networks
暂无分享,去创建一个
[1] Arnold W. M. Smeulders,et al. Tracking by Natural Language Specification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Basura Fernando,et al. Discriminatively Learned Hierarchical Rank Pooling Networks , 2017, International Journal of Computer Vision.
[3] Andrew Zisserman,et al. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Anoop Cherian,et al. Ordered Pooling of Optical Flow Sequences for Action Recognition , 2017, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).
[5] Zhuowen Tu,et al. Aggregated Residual Transformations for Deep Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Tinne Tuytelaars,et al. Rank Pooling for Action Recognition , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Li Fei-Fei,et al. Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos , 2015, International Journal of Computer Vision.
[8] Richard P. Wildes,et al. Spatiotemporal Residual Networks for Video Action Recognition , 2016, NIPS.
[9] Antonio Manuel López Peña,et al. Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition , 2016, ECCV.
[10] Luc Van Gool,et al. Temporal Segment Networks: Towards Good Practices for Deep Action Recognition , 2016, ECCV.
[11] Anoop Cherian,et al. On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization , 2016, ArXiv.
[12] Andrea Vedaldi,et al. Dynamic Image Networks for Action Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Basura Fernando,et al. Learning End-to-end Video Classification with Rank-Pooling , 2016, ICML.
[14] Nuno Vasconcelos,et al. VLAD3: Encoding Dynamics of Deep Features for Action Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Marcus Hutter,et al. Discriminative Hierarchical Rank Pooling for Activity Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Arnold W. M. Smeulders,et al. UvA-DARE (Digital Academic Repository) Siamese Instance Search for Tracking , 2016 .
[17] Andrew Zisserman,et al. Convolutional Two-Stream Network Fusion for Video Action Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Limin Wang,et al. Computer Vision and Image Understanding Bag of Visual Words and Fusion Methods for Action Recognition: Comprehensive Study and Good Practice , 2022 .
[19] Lin Sun,et al. Human Action Recognition Using Factorized Spatio-Temporal Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[20] Silvio Savarese,et al. Action Recognition by Hierarchical Mid-Level Action Elements , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[21] Cordelia Schmid,et al. P-CNN: Pose-Based CNN Features for Action Recognition , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[22] Tinne Tuytelaars,et al. Modeling video evolution for action recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Cees Snoek,et al. What do 15,000 object categories tell us about classifying and localizing actions? , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Alexei A. Efros,et al. Unsupervised Visual Representation Learning by Context Prediction , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[25] Limin Wang,et al. Action recognition with trajectory-pooled deep-convolutional descriptors , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Matthew J. Hausknecht,et al. Beyond short snippets: Deep networks for video classification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Nitish Srivastava,et al. Exploiting Image-trained CNN Architectures for Unconstrained Video Classification , 2015, BMVC.
[28] Nitish Srivastava,et al. Unsupervised Learning of Video Representations using LSTMs , 2015, ICML.
[29] Larry H. Matthies,et al. Pooled motion features for first-person videos , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Andrea Vedaldi,et al. MatConvNet: Convolutional Neural Networks for MATLAB , 2014, ACM Multimedia.
[31] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[32] Bhiksha Raj,et al. Beyond Gaussian Pyramid: Multi-skip Feature Stacking for action recognition , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Jitendra Malik,et al. Finding action tubes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Trevor Darrell,et al. Long-term recurrent convolutional networks for visual recognition and description , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[37] Andrew Zisserman,et al. Improving Human Action Recognition Using Score Distribution and Ranking , 2014, ACCV.
[38] Masoud Mazloom,et al. Conceptlets: Selective Semantics for Classifying Video Events , 2014, IEEE Transactions on Multimedia.
[39] Yu Qiao,et al. Action Recognition with Stacked Fisher Vectors , 2014, ECCV.
[40] Jianxin Wu,et al. Towards Good Practices for Action Video Encoding , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[41] Ling Shao,et al. Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[43] Andrew Zisserman,et al. Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.
[44] Cordelia Schmid,et al. Action Recognition with Improved Trajectories , 2013, 2013 IEEE International Conference on Computer Vision.
[45] Yale Song,et al. Action Recognition by Hierarchical Sequence Summarization , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[46] Ming Yang,et al. 3D Convolutional Neural Networks for Human Action Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[47] Cordelia Schmid,et al. Dense Trajectories and Motion Boundary Descriptors for Action Recognition , 2013, International Journal of Computer Vision.
[48] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[49] Mubarak Shah,et al. UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild , 2012, ArXiv.
[50] Iasonas Kokkinos,et al. Discovering discriminative action parts from mid-level video representations , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[51] Thomas Serre,et al. HMDB: A large video database for human motion recognition , 2011, 2011 International Conference on Computer Vision.
[52] Yang Wang,et al. Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[53] Silvio Savarese,et al. Recognizing human actions by attributes , 2011, CVPR 2011.
[54] Quoc V. Le,et al. Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis , 2011, CVPR 2011.
[55] Luc Van Gool,et al. Does Human Action Recognition Benefit from Pose Estimation? , 2011, BMVC.
[56] Florent Perronnin,et al. Large-scale image retrieval with compressed Fisher vectors , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[57] Mubarak Shah,et al. Human Action Recognition in Videos Using Kinematic Features and Multiple Instance Learning , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[58] Charless C. Fowlkes,et al. Bilinear classifiers for visual recognition , 2009, NIPS.
[59] C. Schmid,et al. Actions in context , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[60] Mubarak Shah,et al. Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[61] Luc Van Gool,et al. Action snippets: How many frames does human action recognition require? , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[62] Matti Pietikäinen,et al. Human Activity Recognition Using a Dynamic Texture Based Method , 2008, BMVC.
[63] Horst Bischof,et al. A Duality Based Approach for Realtime TV-L1 Optical Flow , 2007, DAGM-Symposium.
[64] Cordelia Schmid,et al. Human Detection Using Oriented Histograms of Flow and Appearance , 2006, ECCV.
[65] Martial Hebert,et al. Efficient visual event detection using volumetric features , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[66] Ivan Laptev,et al. On Space-Time Interest Points , 2005, International Journal of Computer Vision.
[67] Yann LeCun,et al. Learning a similarity metric discriminatively, with application to face verification , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[68] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[69] Eli Shechtman,et al. Space-time behavior based correlation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[70] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[71] Jitendra Malik,et al. Recognizing action at a distance , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[72] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[73] Y. Wu,et al. Dynamic Textures , 2003, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[74] James W. Davis,et al. The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[75] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[76] D. Kinghorn. Integrals and derivatives for correlated Gaussian functions using matrix differential calculus , 1996 .