Hierarchical Spatial Sum–Product Networks for Action Recognition in Still Images
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[1] Subhransu Maji,et al. Detecting People Using Mutually Consistent Poselet Activations , 2010, ECCV.
[2] Lin Sun,et al. DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Gang Wang,et al. Scene Parsing With Integration of Parametric and Non-Parametric Models , 2016, IEEE Transactions on Image Processing.
[4] Robert R. Sokal,et al. A statistical method for evaluating systematic relationships , 1958 .
[5] Subhransu Maji,et al. Action recognition from a distributed representation of pose and appearance , 2011, CVPR 2011.
[6] Charless C. Fowlkes,et al. Discriminative models for static human-object interactions , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[7] Ivan Laptev,et al. Recognizing human actions in still images: a study of bag-of-features and part-based representations , 2010, BMVC.
[8] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[9] Gang Wang,et al. Real-time part-based visual tracking via adaptive correlation filters , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Cordelia Schmid,et al. Discriminative spatial saliency for image classification , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[11] Pedro M. Domingos,et al. Sum-product networks: A new deep architecture , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[12] Shuicheng Yan,et al. STAP: Spatial-Temporal Attention-Aware Pooling for Action Recognition , 2015, IEEE Transactions on Circuits and Systems for Video Technology.
[13] Iqbal Gondal,et al. On Temporal Order Invariance for View-Invariant Action Recognition , 2013, IEEE Transactions on Circuits and Systems for Video Technology.
[14] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[15] Pietro Perona,et al. Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition , 2007, International Journal of Computer Vision.
[16] David A. McAllester,et al. Object Detection with Discriminatively Trained Part Based Models , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Yihong Gong,et al. Locality-constrained Linear Coding for image classification , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[18] Gang Wang,et al. Multi-modal feature fusion for action recognition in RGB-D sequences , 2014, 2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP).
[19] Mohamed R. Amer,et al. Sum-product networks for modeling activities with stochastic structure , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[20] Yang Wang,et al. Recognizing human actions from still images with latent poses , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[21] Leonidas J. Guibas,et al. Human action recognition by learning bases of action attributes and parts , 2011, 2011 International Conference on Computer Vision.
[22] Guodong Guo,et al. A survey on still image based human action recognition , 2014, Pattern Recognit..
[23] Adnan Darwiche,et al. A differential approach to inference in Bayesian networks , 2000, JACM.
[24] Gabriel Thomas,et al. Human Activity Recognition using Binary Motion Image and Deep Learning , 2015, Procedia Computer Science.
[25] Xiaogang Wang,et al. A Deep Sum-Product Architecture for Robust Facial Attributes Analysis , 2013, 2013 IEEE International Conference on Computer Vision.
[26] Yang Wang,et al. Unsupervised Discovery of Action Classes , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[27] Gang Wang,et al. Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks , 2015, IEEE Transactions on Image Processing.
[28] David A. McAllester,et al. A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Cordelia Schmid,et al. Expanded Parts Model for Human Attribute and Action Recognition in Still Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[30] Fei-Fei Li,et al. Modeling mutual context of object and human pose in human-object interaction activities , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] Yi Yang,et al. Articulated pose estimation with flexible mixtures-of-parts , 2011, CVPR 2011.
[32] Ivan Laptev,et al. Learning person-object interactions for action recognition in still images , 2011, NIPS.
[33] Yoshua Bengio,et al. Shallow vs. Deep Sum-Product Networks , 2011, NIPS.
[34] Christian Wolf,et al. Sequential Deep Learning for Human Action Recognition , 2011, HBU.
[35] Daniel Lowd,et al. Learning Sum-Product Networks with Direct and Indirect Variable Interactions , 2014, ICML.
[36] Chunheng Wang,et al. Cross-View Action Recognition Using Contextual Maximum Margin Clustering , 2014, IEEE Transactions on Circuits and Systems for Video Technology.
[37] Hao Su,et al. Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification , 2010, NIPS.
[38] Dong Xu,et al. Action Recognition Using Multilevel Features and Latent Structural SVM , 2013, IEEE Transactions on Circuits and Systems for Video Technology.
[39] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[40] Pedro M. Domingos,et al. Discriminative Learning of Sum-Product Networks , 2012, NIPS.
[41] Tian-Tsong Ng,et al. Multimodal Multipart Learning for Action Recognition in Depth Videos , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[42] Gang Wang,et al. Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks , 2015, ArXiv.
[43] Gang Wang,et al. Video Tracking Using Learned Hierarchical Features , 2015, IEEE Transactions on Image Processing.
[44] Fei-Fei Li,et al. Grouplet: A structured image representation for recognizing human and object interactions , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[45] Alessia Saggese,et al. Exploiting the deep learning paradigm for recognizing human actions , 2014, 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
[46] Nazli Ikizler-Cinbis,et al. Learning actions from the Web , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[47] Jenq-Neng Hwang,et al. A Review on Video-Based Human Activity Recognition , 2013, Comput..
[48] Václav Hlavác,et al. Pose primitive based human action recognition in videos or still images , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[49] Jitendra Malik,et al. Poselets: Body part detectors trained using 3D human pose annotations , 2009, 2009 IEEE 12th International Conference on Computer Vision.