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Transformer-based architectures represent the state of the art in sequence modeling tasks like machine translation and language understanding.
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Deep visual-semantic alignments for generating image descriptions
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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CIDEr: Consensus-based Image Description Evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Show and tell: A neural image caption generator
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard S Zemel, and Yoshua Bengio · 2015
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SPICE: Semantic Propositional Image Caption Evaluation
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Graph Attention Networks
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Exploring Visual Relationship for Image Captioning
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nocaps: novel object captioning at scale
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