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Human action-anticipation methods predict what is the future action by observing only a few portion of an action in progress.
A tutorial on support vector regression
Smola, A.J., Schölkopf, B.: · 2004
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You’ll never walk alone: Modeling social behavior for multi-target tracking
Pellegrini, S., Ess, A., Schindler, K., Van Gool, L.: · 2009
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Improving offensive performance through opponent modeling
Laviers, K., Sukthankar, G., Aha, D.W., Molineaux, M., Darken, C., et al.: · 2009
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UT-Interaction Dataset, ICPR contest on Semantic Description of Human Activities (SDHA)
Ryoo, M.S., Aggarwal, J.K.: · 2010
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An overview of contest on semantic description of human activities (sdha) 2010
Ryoo, M., Chen, C.C., Aggarwal, J., Roy-Chowdhury, A.: · 2010
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Human activity prediction: Early recognition of ongoing activities from streaming videos
Ryoo, M.S.: · 2011
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Hmdb: a large video database for human motion recognition
Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.: · 2011
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Predicting human activities using spatio-temporal structure of interest points
Yu, G., Yuan, J., Liu, Z.: · 2012
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Motion history image: its variants and applications
Ahad, M.A.R., Tan, J.K., Kim, H., Ishikawa, S.: · 2012
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Predicting human activities using spatio-temporal structure of interest points
Yu, G., Yuan, J., Liu, Z.: · 2012
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Activity forecasting
Kitani, K.M., Ziebart, B.D., Bagnell, J.A., Hebert, M.: · 2012
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Autoencoders, unsupervised learning, and deep architectures
Baldi, P.: · 2012
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Soomro, K., Zamir, A.R., Shah, M.: · 2012
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Towards understanding action recognition
Jhuang, H., Gall, J., Zuffi, S., Schmid, C., Black, M.J.: · 2013
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A hierarchical representation for future action prediction
Lan, T., Chen, T.C., Savarese, S.: · 2014
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Two-stream convolutional networks for action recognition in videos
Simonyan, K., Zisserman, A.: · 2014
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Prediction of human activity by discovering temporal sequence patterns
Li, K., Fu, Y.: · 2014
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A discriminative model with multiple temporal scales for action prediction
Kong, Y., Kit, D., Fu, Y.: · 2014
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Semi-supervised learning with deep generative models
Kingma, D.P., Mohamed, S., Rezende, D.J., Welling, M.: · 2014
Cited alongside, same era.
Online localization and prediction of actions and interactions
Soomro, K., Idrees, H., Shah, M.: · 2016
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Predicting the where and what of actors and actions through online action localization
Soomro, K., Idrees, H., Shah, M.: · 2016
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Anticipating visual representations from unlabeled video
Vondrick, C., Pirsiavash, H., Torralba, A.: · 2016
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Recurrent neural networks for driver activity anticipation via sensory-fusion architecture
Jain, A., Singh, A., Koppula, H.S., Soh, S., Saxena, A.: · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., Chintala, S.: · 2016
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Conditional generative adversarial nets
Mirza, M., Osindero, S.: · 2014
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Learning structured output representation using deep conditional generative models
Sohn, K., Lee, H., Yan, X.: · 2015
Cited alongside, same era.
Distilling the knowledge in a neural network
Hinton, G., Vinyals, O., Dean, J.: · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
Kingma, D.P., Ba, J.: · 2015
Cited alongside, same era.
Dynamic image networks for action recognition
Bilen, H., Fernando, B., Gavves, E., Vedaldi, A., Gould, S.: · 2016
Cited alongside, same era.
Learning activity progression in lstms for activity detection and early detection
Ma, S., Sigal, L., Sclaroff, S.: · 2016
Cited alongside, same era.
Sadegh Aliakbarian, M., Sadat Saleh, F., Salzmann, M., Fernando, B., Petersson, L., Andersson, L.: · 2017
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Action recognition with dynamic image networks
Bilen, H., Fernando, B., Gavves, E., Vedaldi, A.: · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Carreira, J., Zisserman, A.: · 2017
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Online real-time multiple spatiotemporal action localisation and prediction
Singh, G., Saha, S., Sapienza, M., Torr, P.H.S., Cuzzolin, F.: · 2017
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Red: Reinforced encoder-decoder networks for action anticipation
Gao, J., Yang, Z., Nevatia, R.: · 2017
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Rank pooling for action recognition
Fernando, B., Gavves, E., Oramas, J., Ghodrati, A., Tuytelaars, T.: · 2017
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Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C., Ioffe, S., Vanhoucke, V., Alemi, A.A.: · 2017
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