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Deep convolutional networks have achieved great success for object recognition in still images.
A duality based approach for realtime tv- L 1 L^{1} optical flow
C. Zach, T. Pock, and H. Bischof · 2007
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ImageNet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and F. Li · 2009
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 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
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THUMOS challenge: Action recognition with a large number of classes, 2013
Y.-G. Jiang, J. Liu, A. Roshan Zamir, I. Laptev, M. Piccardi, M. Shah, and R. Sukthankar · 2013
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Image classification with the fisher vector: Theory and practice
J. Sánchez, F. Perronnin, T. Mensink, and J. J. Verbeek · 2013
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Action recognition with improved trajectories
H. Wang and C. Schmid · 2013
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Mining motion atoms and phrases for complex action recognition
L. Wang, Y. Qiao, and X. Tang · 2013
Cited alongside, same era.
Motionlets: Mid-level 3D parts for human motion recognition
L. Wang, Y. Qiao, and X. Tang · 2013
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.
Bag of visual words and fusion methods for action recognition: Comprehensive study and good practice
X. Peng, L. Wang, X. Wang, and Y. Qiao · 2014
Cited alongside, same era.
Two-stream convolutional networks for action recognition in videos
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Later among the works it cites.
THUMOS challenge: Action recognition with a large number of classes
A. Gorban, H. Idrees, Y.-G. Jiang, A. Roshan Zamir, I. Laptev, M. Shah, and R. Sukthankar · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Beyond gaussian pyramid: Multi-skip feature stacking for action recognition
Z. Lan, M. Lin, X. Li, A. G. Hauptmann, and B. Raj · 2015
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Beyond short snippets: Deep networks for video classification
J. Y.-H. Ng, M. Hausknecht, S. Vijayanarasimhan, O. Vinyals, R. Monga, and G. Toderici · 2015
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Action recognition with trajectory-pooled deep-convolutional descriptors
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K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. B. Girshick, S. Guadarrama, and T. Darrell
Cited in the paper.
L. Wang, Y. Qiao, and X. Tang · 2015
Closest in time.
CUHK&SIAT submission for THUMOS15 action recognition challenge
L. Wang, Z. Wang, Y. Xiong, and Y. Qiao · 2015
Closest in time.