Fetching the paper…
Reading the bibliography…
Deep Recurrent Neural Network architectures, though remarkably capable at modeling sequences, lack an intuitive high-level spatio-temporal structure.
Globally trained handwritten word recognizer using spatial representation, convolutional neural networks, and hidden markov models
Y. Bengio, Y. LeCun, and D. Henderson · 1994
Earlier work this paper cites.
Learning task-dependent distributed representations by backpropagation through structure
C. Goller and A. Kuchler · 1996
Earlier work this paper cites.
Global training of document processing systems using graph transformer networks
L. Bottou, Y. Bengio, and Y. LeCun · 1997
Earlier work this paper cites.
Factor graphs and the sum-product algorithm
F. R. Kschischang, B. J. Frey, and H.-A. Loeliger · 2001
Earlier work this paper cites.
Discriminative probabilistic models for relational data
B. Taskar, P. Abbeel, and D. Koller · 2002
Earlier work this paper cites.
Conditional random fields for object recognition
A. Quattoni, M. Collins, and T. Darrell · 2004
Earlier work this paper cites.
Markov logic networks
M. Richardson and P. Domingos · 2006
Earlier work this paper cites.
Modeling human motion using binary latent variables
G. W. Taylor, G. E. Hinton, and S. T. Roweis · 2006
Earlier work this paper cites.
Conditional random fields for activity recognition
D. L. Vail, M. M. Veloso, and J. D. Lafferty · 2007
Earlier work this paper cites.
A discriminatively trained, multiscale, deformable part model
P. Felzenszwalb, D. McAllester, and D. Ramanan · 2008
Earlier work this paper cites.
Learning realistic human actions from movies
I. Laptev, M. Marszałek, C. Schmid, and B. Rozenfeld · 2008
Earlier work this paper cites.
Key object driven multi-category object recognition, localization and tracking using spatio-temporal context
Y. Li and R. Nevatia · 2008
Earlier work this paper cites.
Topologically-constrained latent variable models
R. Urtasun, D. J. Fleet, A. Geiger, J. Popović, T. J. Darrell, and N. D. Lawrence · 2008
Earlier work this paper cites.
Gaussian process dynamical models for human motion
J. M. Wang, D. J. Fleet, and A. Hertzmann · 2008
Earlier work this paper cites.
Curriculum learning
Y. Bengio, J. Louradour, R. Collobert, and J. Weston · 2009
Earlier work this paper cites.
Mosift: Recognizing human actions in surveillance videos
M. Chen and A. Hauptmann · 2009
Earlier work this paper cites.
Observing human-object interactions: Using spatial and functional compatibility for recognition
A. Gupta, A. Kembhavi, and L. S. Davis · 2009
Earlier work this paper cites.
Cutting-plane training of structural svms
T. Joachims, T. Finley, and C.-N. J. Yu · 2009
Earlier work this paper cites.
Probabilistic graphical models: principles and techniques
D. Koller and N. Friedman · 2009
Earlier work this paper cites.
Factorie: Probabilistic programming via imperatively defined factor graphs
A. McCallum, K. Schultz, and S. Singh · 2009
Earlier work this paper cites.
The recurrent temporal restricted boltzmann machine
I. Sutskever, G. Hinton, and G. Taylor · 2009
Earlier work this paper cites.
Factored conditional restricted boltzmann machines for modeling motion style
G. Taylor and G. E. Hinton · 2009
Earlier work this paper cites.
Dynamical binary latent variable models for 3d human pose tracking
G. Taylor, L. Sigal, D. J. Fleet, and G. E. Hinton · 2010
Earlier work this paper cites.
Learning spatiotemporal graphs of human activities
W. Brendel and S. Todorovic · 2011
Cited alongside, same era.
A spatio-temporal probabilistic model for multi-sensor multi-class object recognition
B. Douillard, D. Fox, and F. Ramos · 2011
Cited alongside, same era.
Track to the future: Spatio-temporal video segmentation with long-range motion cues
J. Lezama, K. Alahari, J. Sivic, and I. Laptev · 2011
Cited alongside, same era.
Human action segmentation and recognition using discriminative semi-markov models
Q. Shi, L. Cheng, L. Wang, and A. Smola · 2011
Cited alongside, same era.
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
R. Socher, C. C. Lin, A. Y. Ng, and C. D. Manning · 2011
Cited alongside, same era.
An introduction to conditional random fields
C. Sutton and A. McCallum · 2011
Translating videos to natural language using deep recurrent neural networks
S. Venugopalan, H. Xu, J. Donahue, M. Rohrbach, R. Mooney, and K. Saenko · 2014
Later among the works it cites.
Panda: Pose aligned networks for deep attribute modeling
N. Zhang, M. Paluri, M. A. Ranzato, T. Darrell, and L. Bourdev · 2014
Later among the works it cites.
Overtaking vehicle detection using a spatio-temporal crf
X. Zhang, P. Jiang, and F. Wang · 2014
Later among the works it cites.
Scene labeling with lstm recurrent neural networks
W. Byeon, T. Breuel, F. Raue, and M. Liwicki · 2015
Closest in time.
Learning deep structured models
L. C. Chen, A. Schwing, A. L. Yuille, and R. Urtasun · 2015
Closest in time.
Mind’s eye: A recurrent visual representation for image caption generation
X. Chen and C. L. Zitnick · 2015
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Efficient inference in fully connected crfs with gaussian edge potentials
P. Krähenbühl and V. Koltun · 2012
Cited alongside, same era.
Generating sequences with recurrent neural networks
A. Graves · 2013
Cited alongside, same era.
Beyond geometric path planning: Learning context-driven user preferences via sub-optimal feedback
A. Jain, S. Sharma, and A. Saxena · 2013
Cited alongside, same era.
Learning human activities and object affordances from rgb-d videos
H. Koppula, R. Gupta, and A. Saxena · 2013
Cited alongside, same era.
Anticipating human activities using object affordances for reactive robotic response
H. Koppula and A. Saxena · 2013
Cited alongside, same era.
Learning spatio-temporal structure from rgb-d videos for human activity detection and anticipation
H. Koppula and A. Saxena · 2013
Cited alongside, same era.
Closest in time.
Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. A. Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
Closest in time.
Hierarchical recurrent neural network for skeleton based action recognition
Y. Du, W. Wang, and L. Wang · 2015
Closest in time.
Recurrent network models for human dynamics
K. Fragkiadaki, S. Levine, P. Felsen, and J. Malik · 2015
Closest in time.
Fully connected deep structured networks
A. G. S. G and R. Urtasun · 2015
Closest in time.
Fast r-cnn
R. Girshick · 2015
Closest in time.
Car that knows before you do: Anticipating maneuvers via learning temporal driving models
A. Jain, H. S. Koppula, B. Raghavan, S. Soh, and A. Saxena · 2015
Closest in time.
Objects2action: Classifying and localizing actions without any video example
M. Jain, J. C. van Gemert, T. Mensink, and C. Snoek · 2015
Closest in time.
Visualizing and understanding recurrent networks
A. Karpathy, J. Johnson, and F. F. Li · 2015
Closest in time.
Anticipating human activities using object affordances for reactive robotic response
H. Koppula and A. Saxena · 2015
Closest in time.
Maximum-margin structured learning with deep networks for 3d human pose estimation
S. Li, W. Zhang, and A. B. Chan · 2015
Closest in time.
Efficient piecewise training of deep structured models for semantic segmentation
G. Lin, C. Shen, I. Reid, et al · 2015
Closest in time.
Semantic image segmentation via deep parsing network
Z. Liu, X. Li, P. Luo, C. C. Loy, and X. Tang · 2015
Closest in time.
Unsupervised learning of video representations using lstms
N. Srivastava, E. Mansimov, and R. Salakhutdinov · 2015
Closest in time.
Conditional random fields as recurrent neural networks
S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. Torr · 2015
Closest in time.
Recurrent network models for human dynamics
K. Fragkiadaki, S. Levine, P. Felsen, and J. Malik · 2015
Closest in time.
Car that knows before you do: Anticipating maneuvers via learning temporal driving models
A. Jain, H. S. Koppula, B. Raghavan, S. Soh, and A. Saxena · 2015
Closest in time.