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Detecting activities in untrimmed videos is an important but challenging task.
On space-time interest points
I. Laptev · 2005
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Action snippets: How many frames does human action recognition require?
K. Schindler and L. Van Gool · 2008
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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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Recognition using regions
C. Gu, J. J. Lim, P. Arbeláez, and J. Malik · 2009
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Segmentation as selective search for object recognition
K. E. Van de Sande, J. R. Uijlings, T. Gevers, and A. W. Smeulders · 2011
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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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Temporal localization of actions with actoms
A. Gaidon, Z. Harchaoui, and C. Schmid · 2013
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Action and event recognition with fisher vectors on a compact feature set
D. Oneata, J. Verbeek, and C. Schmid · 2013
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Combining the right features for complex event recognition
K. Tang, B. Yao, L. Fei-Fei, and D. Koller · 2013
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Action recognition with improved trajectories
H. Wang and C. Schmid · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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THUMOS challenge: Action recognition with a large number of classes
Y.-G. Jiang, J. Liu, A. Roshan Zamir, G. Toderici, I. Laptev, M. Shah, and R. Sukthankar · 2014
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Fast saliency based pooling of fisher encoded dense trajectories
S. Karaman, L. Seidenari, and A. Del Bimbo · 2014
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Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei · 2014
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The lear submission at thumos 2014
D. Oneata, J. Verbeek, and C. Schmid · 2014
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Two-stream convolutional networks for action recognition in videos
K. Simonyan and A. Zisserman · 2014
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Action recognition and detection by combining motion and appearance features
L. Wang, Y. Qiao, and X. Tang · 2014
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Edge boxes: Locating object proposals from edges
C. L. Zitnick and P. Dollár · 2014
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Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. Anne Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
Action recognition with trajectory-pooled deep-convolutional descriptors
L. Wang, Y. Qiao, and X. Tang · 2015
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Daps: Deep action proposals for action understanding
V. Escorcia, F. Caba Heilbron, J. C. Niebles, and B. Ghanem · 2016
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Fast temporal activity proposals for efficient detection of human actions in untrimmed videos
B. G. Fabian Caba Heilbron, Juan Carlos Niebles · 2016
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Temporal activity detection in untrimmed videos with recurrent neural networks
A. Montes, A. Salvador, S. Pascual, and X. Giro-i Nieto · 2016
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Temporal action detection using a statistical language model
A. Richard and J. Gall · 2016
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Temporal action localization in untrimmed videos via multi-stage CNNs
Z. Shou, D. Wang, and S.-F. Chang · 2016
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Cited alongside, same era.
Activitynet: A large-scale video benchmark for human activity understanding
B. G. Fabian Caba Heilbron, Victor Escorcia and J. C. Niebles · 2015
Cited alongside, same era.
Fast r-cnn
R. Girshick · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Bag-of-fragments: Selecting and encoding video fragments for event detection and recounting
P. Mettes, J. C. van Gemert, S. Cappallo, T. Mensink, and C. G. Snoek · 2015
Cited alongside, same era.
Beyond short snippets: Deep networks for video classification
J. Y.-H. Ng, M. Hausknecht, S. Vijayanarasimhan, O. Vinyals, R. Monga, and G. Toderici · 2015
Cited alongside, same era.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Cited alongside, same era.
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A multi-stream bi-directional recurrent neural network for fine-grained action detection
B. Singh, T. K. Marks, M. Jones, O. Tuzel, and M. Shao · 2016
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Untrimmed video classification for activity detection: submission to activitynet challenge
G. Singh and F. Cuzzolin · 2016
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Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 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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UTS at activitynet 2016
R. Wang and D. Tao · 2016
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End-to-end learning of action detection from frame glimpses in videos
S. Yeung, O. Russakovsky, G. Mori, and L. Fei-Fei · 2016
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Temporal action localization with pyramid of score distribution features
J. Yuan, B. Ni, X. Yang, and A. A. Kassim · 2016
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Real-time action recognition with enhanced motion vector CNNs
B. Zhang, L. Wang, Z. Wang, Y. Qiao, and H. Wang · 2016
Later among the works it cites.