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We present an approach named CurlingNet that can measure the semantic distance of composition of image-text embedding.
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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Adam: A Method for Stochastic Optimization
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Relja Arandjelovic, Petr Gronat, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2016
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Multimodal compact bilinear pooling for visual question answering and visual grounding
Akira Fukui, Dong Huk Park, Daylen Yang, Anna Rohrbach, Trevor Darrell, and Marcus Rohrbach · 2016
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Deep Residual Learning for Image Recognition
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Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
Dual encoding for zero-example video retrieval
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The fashion iq dataset: Retrieving images by combining side information and relative natural language feedback
Xiaoxiao Guo, Hui Wu, Yupeng Gao, Steven Rennie, and Rogerio Feris · 2019
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Use what you have: Video retrieval using representations from collaborative experts
Y. Liu, S. Albanie, A. Nagrani, and A. Zisserman · 2019
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Fashion-Gen: The Generative Fashion Dataset and Challenge
N. Rostamzadeh, S. Hosseini, T. Boquet, W. Stokowiec, Y. Zhang, C. Jauvin, and C. Pal · 2019
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Composing text and image for image retrieval-an empirical odyssey
Nam Vo, Lu Jiang, Chen Sun, Kevin Murphy, Li-Jia Li, Li Fei-Fei, and James Hays · 2019
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Yinfei Yang, Gustavo Hernandez Abrego, Steve Yuan, Mandy Guo, Qinlan Shen, Daniel Cer, Yun-hsuan Sung, Brian Strope, and Ray Kurzweil · 2019
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