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Despite the fact that many 3D human activity benchmarks being proposed, most existing action datasets focus on the action recognition tasks for the segmented videos.
Learning realistic human actions from movies
I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld · 2008
Earlier work this paper cites.
Action recognition based on a bag of 3D points
W. Li, Z. Zhang, and Z. Liu · 2010
Earlier work this paper cites.
Improving the fisher kernel for large-scale image classification
F. Perronnin, J. Sánchez, and T. Mensink · 2010
Earlier work this paper cites.
Human activity prediction: Early recognition of ongoing activities from streaming videos
M. S. Ryoo · 2011
Earlier work this paper cites.
Human activity detection from RGBD images
J. Sung, C. Ponce, B. Selman, and A. Saxena · 2011
Earlier work this paper cites.
Action recognition by dense trajectories
H. Wang, A. Kläser, C. Schmid, and C.-L. Liu · 2011
Earlier work this paper cites.
G3D: A gaming action dataset and real time action recognition evaluation framework
V. Bloom, D. Makris, and V. Argyriou · 2012
Earlier work this paper cites.
Human daily action analysis with multi-view and color-depth data
Z. Cheng, L. Qin, Y. Ye, Q. Huang, and Q. Tian · 2012
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UCF101: A dataset of 101 human actions classes from videos in the wild
K. Soomro, A. R. Zamir, and M. Shah · 2012
Earlier work this paper cites.
Unstructured human activity detection from RGBD images
J. Sung, C. Ponce, B. Selman, and A. Saxena · 2012
Earlier work this paper cites.
Mining actionlet ensemble for action recognition with depth cameras
J. Wang, Z. Liu, Y. Wu, and J. Yuan · 2012
Earlier work this paper cites.
View invariant human action recognition using histograms of 3D joints
L. Xia, C.-C. Chen, and J. Aggarwal · 2012
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Two-person interaction detection using body-pose features and multiple instance learning
K. Yun, J. Honorio, D. Chattopadhyay, T. L. Berg, and D. Samaras · 2012
Earlier work this paper cites.
Non-intrusive human activity monitoring in a smart home environment
S. M. Amiri, M. T. Pourazad, P. Nasiopoulos, and V. C. Leung · 2013
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A survey of human motion analysis using depth imagery
L. Chen, H. Wei, and J. Ferryman · 2013
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Human action recognition using a temporal hierarchy of covariance descriptors on 3D joint locations
M. E. Hussein, M. Torki, M. A. Gowayyed, and M. El-Saban · 2013
Earlier work this paper cites.
RGBD-hudaact: A color-depth video database for human daily activity recognition
B. Ni, G. Wang, and P. Moulin · 2013
Earlier work this paper cites.
Berkeley mhad: A comprehensive multimodal human action database
F. Ofli, R. Chaudhry, G. Kurillo, R. Vidal, and R. Bajcsy · 2013
Earlier work this paper cites.
Hon4D: Histogram of oriented 4D normals for activity recognition from depth sequences
O. Oreifej and Z. Liu · 2013
Earlier work this paper cites.
Spatiotemporal deformable part models for action detection
Y. Tian, R. Sukthankar, and M. Shah · 2013
Cited alongside, same era.
Action recognition with improved trajectories
H. Wang and C. Schmid · 2013
Cited alongside, same era.
Modeling 4D human-object interactions for event and object recognition
P. Wei, Y. Zhao, N. Zheng, and S.-C. Zhu · 2013
Cited alongside, same era.
Concurrent action detection with structural prediction
P. Wei, N. Zheng, Y. Zhao, and S.-C. Zhu · 2013
Cited alongside, same era.
The moving pose: An efficient 3D kinematics descriptor for low-latency action recognition and detection
M. Zanfir, M. Leordeanu, and C. Sminchisescu · 2013
Cited alongside, same era.
Human activity recognition from 3D data: A review
J. K. Aggarwal and L. Xia · 2014
Cited alongside, same era.
Hierarchical recurrent neural network for skeleton based action recognition
Y. Du, W. Wang, and L. Wang · 2015
Later among the works it cites.
Motion recognition employing multiple kernel learning of fisher vectors using local skeleton features
Y. Goutsu, W. Takano, and Y. Nakamura · 2015
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Coupled hidden conditional random fields for RGB-D human action recognition
A.-A. Liu, W.-Z. Nie, Y.-T. Su, L. Ma, T. Hao, and Z.-X. Yang · 2015
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Real-time multi-scale action detection from 3D skeleton data
A. Sharaf, M. Torki, M. E. Hussein, and M. El-Saban · 2015
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Cuhk&siat submission for THUMOS15 action recognition challenge
L. Wang, Z. Wang, Y. Xiong, and Y. Qiao · 2015
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Watch-n-patch: Unsupervised understanding of actions and relations
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Max-margin early event detectors
M. Hoai and F. De la Torre · 2014
Cited alongside, same era.
Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei · 2014
Cited alongside, same era.
Discriminative hierarchical modeling of spatio-temporally composable human activities
I. Lillo, A. Soto, and J. Carlos Niebles · 2014
Cited alongside, same era.
Hopc: Histogram of oriented principal components of 3D pointclouds for action recognition
H. Rahmani, A. Mahmood, D. Q. Huynh, and A. Mian · 2014
Cited alongside, same era.
Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. S. Bernstein, A. C. Berg, and F. Li · 2014
Cited alongside, same era.
Two-stream convolutional networks for action recognition in videos
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
C. Wu, J. Zhang, S. Savarese, and A. Saxena · 2015
Later among the works it cites.
Modeling spatial-temporal clues in a hybrid deep learning framework for video classification
Z. Wu, X. Wang, Y.-G. Jiang, H. Ye, and X. Xue · 2015
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RGB-D datasets using Microsoft Kinect or similar sensors: a survey
Z. Cai, J. Han, L. Liu, and L. Shao · 2016
Later among the works it cites.
Online Action Detection
R. De Geest, E. Gavves, A. Ghodrati, Z. Li, C. Snoek, and T. Tuytelaars · 2016
Later among the works it cites.
Online human action detection using joint classification-regression recurrent neural networks
Y. Li, C. Lan, J. Xing, W. Zeng, C. Yuan, and J. Liu · 2016
Later among the works it cites.
Histogram of oriented principal components for cross-view action recognition
H. Rahmani, A. Mahmood, D. Huynh, and A. Mian · 2016
Later among the works it cites.
NTU RGB+D: A large scale dataset for 3D human activity analysis
A. Shahroudy, J. Liu, T.-T. Ng, and G. Wang · 2016
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Multimodal multipart learning for action recognition in depth videos
A. Shahroudy, T.-T. Ng, Q. Yang, and G. Wang · 2016
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An end-to-end spatio-temporal attention model for human action recognition from skeleton data
S. Song, C. Lan, J. Xing, W. Zeng, and J. Liu · 2016
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Inception-v4, Inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, V. Vanhoucke, and A. Alemi · 2016
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Rolling rotations for recognizing human actions from 3D skeletal data
R. Vemulapalli and R. Chellapa · 2016
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Temporal segment networks: towards good practices for deep action recognition
L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. Van Gool · 2016
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RGB-D-based action recognition datasets: A survey
J. Zhang, W. Li, P. O. Ogunbona, P. Wang, and C. Tang · 2016
Later among the works it cites.
Co-occurrence feature learning for skeleton based action recognition using regularized deep LSTM networks
W. Zhu, C. Lan, J. Xing, W. Zeng, Y. Li, L. Shen, and X. Xie · 2016
Later among the works it cites.