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In this paper, we present an adaptation of the sequence-to-sequence model for structured output prediction in vision tasks.
Pictorial structures for object recognition
Felzenszwalb, P.F., Huttenlocher, D.P.: · 2005
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Learning to parse images of articulated bodies
Ramanan, D.: · 2006
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Search-based structured prediction
Daumé Iii, H., Langford, J., Marcu, D.: · 2009
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Pictorial structures revisited: People detection and articulated pose estimation
Andriluka, M., Roth, S., Schiele, B.: · 2009
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Better appearance models for pictorial structures
Eichner, M., Ferrari, V.: · 2009
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An efficient algorithm for easy-first non-directional dependency parsing
Goldberg, Y., Elhadad, M.: · 2010
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A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Ross, S., Gordon, G.J., Bagnell, J.A.: · 2010
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Rectified linear units improve restricted boltzmann machines
Nair, V., Hinton, G.E.: · 2010
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Articulated pose estimation with flexible mixtures-of-parts
Yang, Y., Ramanan, D.: · 2011
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Learning effective human pose estimation from inaccurate annotation
Johnson, S., Everingham, M.: · 2011
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Exploring the spatial hierarchy of mixture models for human pose estimation
Tian, Y., Zitnick, C.L., Narasimhan, S.G.: · 2012
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Articulated human detection with flexible mixtures-of-parts
Yang, Y., Ramanan, D.: · 2012
Earlier work this paper cites.
Diagnosing error in object detectors
Hoiem, D., Chodpathumwan, Y., Dai, Q.: · 2012
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Beyond physical connections: Tree models in human pose estimation
Wang, F., Li, Y.: · 2013
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Modec: Multimodal decomposable models for human pose estimation
Sapp, B., Taskar, B.: · 2013
Cited alongside, same era.
Poselet conditioned pictorial structures
Pishchulin, L., Andriluka, M., Gehler, P., Schiele, B.: · 2013
Cited alongside, same era.
From actemes to action: A strongly-supervised representation for detailed action understanding
Zhang, W., Zhu, M., Derpanis, K.: · 2013
Cited alongside, same era.
Sequence to sequence learning with neural networks
Sutskever, I., Vinyals, O., Le, Q.V.: · 2014
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., Bengio, Y.: · 2014
Cited alongside, same era.
Deeppose: Human pose estimation via deep neural networks
Toshev, A., Szegedy, C.: · 2014
Order Matters: Sequence to sequence for sets
Vinyals, O., Bengio, S., Kudlur, M.: · 2015
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Human pose estimation with iterative error feedback
Carreira, J., Agrawal, P., Fragkiadaki, K., Malik, J.: · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A.C., Salakhutdinov, R., Zemel, R.S., Bengio, Y.: · 2015
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Scheduled sampling for sequence prediction with recurrent neural networks
Bengio, S., Vinyals, O., Jaitly, N., Shazeer, N.: · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S., Szegedy, C.: · 2015
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Cited alongside, same era.
Pose machines: Articulated pose estimation via inference machines
Ramakrishna, V., Munoz, D., Hebert, M., Bagnell, J.A., Sheikh, Y.: · 2014
Cited alongside, same era.
2d human pose estimation: New benchmark and state of the art analysis
Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: · 2014
Cited alongside, same era.
Chan, W., Jaitly, N., Le, Q.V., Vinyals, O.: · 2015
Cited alongside, same era.
Show and tell: A neural image caption generator
Vinyals, O., Toshev, A., Bengio, S., Erhan, D.: · 2015
Cited alongside, same era.
Learning to generate chairs with convolutional neural networks
Dosovitskiy, A., Tobias Springenberg, J., Brox, T.: · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
Cited alongside, same era.
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: · 2015
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Efficient object localization using convolutional networks
Tompson, J., Goroshin, R., Jain, A., LeCun, Y., Bregler, C.: · 2015
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Joint action recognition and pose estimation from video
Xiaohan Nie, B., Xiong, C., Zhu, S.C.: · 2015
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Convolutional pose machines
Wei, S.E., Ramakrishna, V., Kanade, T., Sheikh, Y.: · 2016
Closest in time.
Stacked hourglass networks for human pose estimation
Newell, A., Yang, K., Deng, J.: · 2016
Closest in time.
Bottom-up and top-down reasoning with hierarchical rectified gaussians
Hu, P., Ramanan, D.: · 2016
Closest in time.
Deepcut: Joint subset partition and labeling for multi person pose estimation
Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., Schiele, B.: · 2016
Closest in time.
Human pose estimation using deep consensusvoting
Lifshitz, I., Fetaya, E., Ullman, S.: · 2016
Closest in time.