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We address the problem of affordance reasoning in diverse scenes that appear in the real world.
The ecological approach to visual perception
J. J. Gibson · 1979
Earlier work this paper cites.
Visual object action recognition: inferring object affordances from human demonstration
H. Kjellstrom, J. Romero, and D. Kragic · 2010
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What makes a chair a chair?
H. Grabner, J. Gall, and L. V. Gool · 2011
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Hallucinated humans as the hidden context for labeling 3d scenes
Y. Jiang, H. S. Koppula, and A. Saxena · 2013
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Discovering object functionality
B. Yao, J. Ma, and L. Fei-Fei · 2013
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Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2014
Earlier work this paper cites.
Reasoning about object affordances in a knowledge base representation
Y. Zhu, A. Fathi, and L. Fei-Fei · 2014
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
L. F.-F. Andrej Karpathy · 2015
Earlier work this paper cites.
Mining semantic affordances of visual object categories
Y.-W. Chao, Z. Wang, R. Mihalcea, and J. Deng · 2015
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
D. Duvenaud, D. Maclaurin, J. Aguilera-Iparraguirre, R. Gómez-Bombarelli, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio · 2015
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Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Joint discovery of object states and manipulating actions
J.-B. Alayrac, J. Sivic, I. Laptev, and S. Lacoste-Julien · 2017
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Interpnet: Neural introspection for interpretable deep learning
S. Barratt · 2017
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Show, adapt and tell: Adversarial training of cross-domain image captioner
T.-H. Chen, Y.-H. Liao, C.-Y. Chuang, W.-T. Hsu, J. Fu, and M. Sun · 2017
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Towards diverse and natural image descriptions via a conditional gan
B. Dai, S. Fidler, R. Urtasun, and D. Lin · 2017
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Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
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Situation recognition with graph neural networks
R. Li, M. Tapaswi, R. Liao, J. Jia, R. Urtasun, and S. Fidler · 2017
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Densecap: Fully convolutional localization networks for dense captioning
J. Johnson, A. Karpathy, and L. Fei-Fei · 2016
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Gated Graph Sequence Neural Networks
Y. Li, D. Tarlow, M. Brockschmidt, and R. Zemel · 2016
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Semantic object parsing with graph lstm
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Learning social affordance for human-robot interaction
T. Shu, M. S. Ryoo, and S.-C. Zhu · 2016
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Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
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Situation recognition with graph neural networks
R. Li1, M. Tapaswi, R. Liao, J. Jia, R. Urtasun, and S. Fidler · 2017
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Fully convolutional instance-aware semantic segmentation
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3d graph neural networks for rgbd semantic segmentation
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Scene parsing through ade20k dataset
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