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Describing what has changed in a scene can be useful to a user, but only if generated text focuses on what is semantically relevant.
Long short-term memory
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Bleu: a method for automatic evaluation of machine translation
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A review of the automated detection of change in serial imaging studies of the brain
J. Patriarche and B. Erickson · 2004
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Image change detection algorithms: a systematic survey
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Changedetection. net: A new change detection benchmark dataset
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A latent analysis of earth surface dynamic evolution using change map time series
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Neural machine translation by jointly learning to align and translate
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J. Tian, S. Cui, and P. Reinartz · 2014
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Cdnet 2014: An expanded change detection benchmark dataset
Y. Wang, P.-M. Jodoin, F. Porikli, J. Konrad, Y. Benezeth, and P. Ishwar · 2014
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Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio · 2015
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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
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Fine-grained change detection of misaligned scenes with varied illuminations
W. Feng, F.-P. Tian, Q. Zhang, N. Zhang, L. Wan, and J. Sun · 2015
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Large-scale damage detection using satellite imagery
L. Gueguen and R. Hamid · 2015
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Change detection from a street image pair using cnn features and superpixel segmentation
K. Sakurada and T. Okatani · 2015
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R. Vedantam, C. Lawrence Zitnick, and D. Parikh · 2015
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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2015
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Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, R. Zemel, and Y. Bengio · 2015
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Spice: Semantic propositional image caption evaluation
P. Anderson, B. Fernando, M. Johnson, and S. Gould · 2016
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Reasoning about pragmatics with neural listeners and speakers
J. Andreas and D. Klein · 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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Generating visual explanations
L. A. Hendricks, Z. Akata, M. Rohrbach, J. Donahue, B. Schiele, and T. Darrell · 2016
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Semantic change detection with hypermaps
H. Kataoka, S. Shirakabe, Y. Miyashita, A. Nakamura, K. Iwata, and Y. Satoh · 2016
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Hierarchical question-image co-attention for visual question answering
J. Lu, J. Yang, D. Batra, and D. Parikh · 2016
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Dual attention networks for multimodal reasoning and matching
Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
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Dense optical flow based change detection network robust to difference of camera viewpoints
K. Sakurada, W. Wang, N. Kawaguchi, and R. Nakamura · 2017
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R. Vedantam, S. Bengio, K. Murphy, D. Parikh, and G. Chechik · 2017
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A joint speakerlistener-reinforcer model for referring expressions
L. Yu, H. Tan, M. Bansal, and T. L. Berg · 2017
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Street-view change detection with deconvolutional networks
P. F. Alcantarilla, S. Stent, G. Ros, R. Arroyo, and R. Gherardi · 2018
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H. Nam, J.-W. Ha, and J. Kim · 2016
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Areas of attention for image captioning
M. Pedersoli, T. Lucas, C. Schmid, and J. Verbeek · 2016
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Precise deterministic change detection for smooth surfaces
S. Stent, R. Gherardi, B. Stenger, and R. Cipolla · 2016
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Stacked attention networks for image question answering
Z. Yang, X. He, J. Gao, L. Deng, and A. Smola · 2016
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A generalized statistical model for binary change detection in multispectral images
M. Zanetti and L. Bruzzone · 2016
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How far can you get by combining change detection algorithms?
S. Bianco, G. Ciocca, and R. Schettini · 2017
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Aligning where to see and what to tell: Image captioning with region-based attention and scene-specific contexts
K. Fu, J. Jin, R. Cui, F. Sha, and C. Zhang · 2017
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P. Anderson, X. He, C. Buehler, D. Teney, M. Johnson, S. Gould, and L. Zhang · 2018
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Pragmatically informative image captioning with character-level reference
R. Cohn-Gordon, N. Goodman, and C. Potts · 2018
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Keep drawing it: Iterative language-based image generation and editing
A. El-Nouby, S. Sharma, H. Schulz, D. Hjelm, L. E. Asri, S. E. Kahou, Y. Bengio, and G. W. Taylor · 2018
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Grounding visual explanations
L. A. Hendricks, R. Hu, T. Darrell, and Z. Akata · 2018
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Explainable neural computation via stack neural module networks
R. Hu, J. Andreas, T. Darrell, and K. Saenko · 2018
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Learning to describe differences between pairs of similar images
H. Jhamtani and T. Berg-Kirkpatrick · 2018
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Change detection in heterogenous remote sensing images via homogeneous pixel transformation
Z. Liu, G. Li, G. Mercier, Y. He, and Q. Pan · 2018
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Neural baby talk
J. Lu, J. Yang, D. Batra, and D. Parikh · 2018
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Discriminability objective for training descriptive captions
R. Luo, B. Price, S. Cohen, and G. Shakhnarovich · 2018
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Transparency by design: Closing the gap between performance and interpretability in visual reasoning
D. Mascharka, P. Tran, R. Soklaski, and A. Majumdar · 2018
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Fast image-based geometric change detection given a 3d model
E. Palazzolo and C. Stachniss · 2018
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Multimodal explanations: Justifying decisions and pointing to the evidence
D. H. Park, L. A. Hendricks, Z. Akata, A. Rohrbach, B. Schiele, T. Darrell, and M. Rohrbach · 2018
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Film: Visual reasoning with a general conditioning layer
E. Perez, F. Strub, H. de Vries, V. Dumoulin, and A. C. Courville · 2018
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Top-down neural attention by excitation backprop
J. Zhang, S. A. Bargal, Z. Lin, J. Brandt, X. Shen, and S. Sclaroff · 2018
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Clevr-dialog: A diagnostic dataset for multi-round reasoning in visual dialog
S. Kottur, J. M. Moura, D. Parikh, D. Batra, and M. Rohrbach · 2019
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Clevr-ref+: Diagnosing visual reasoning with referring expressions
R. Liu, C. Liu, Y. Bai, and A. Yuille · 2019
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