Semantic Compositional Networks for Visual Captioning
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Zhe Gan | Jianfeng Gao | Li Deng | Chuang Gan | Lawrence Carin | Xiaodong He | Yunchen Pu | Kenneth Tran | L. Carin | Jianfeng Gao | Xiaodong He | L. Deng | Chuang Gan | Zhe Gan | Yunchen Pu | Kenneth Tran
[1] Ying Zhang,et al. On Multiplicative Integration with Recurrent Neural Networks , 2016, NIPS.
[2] Xu Jia,et al. Guiding the Long-Short Term Memory Model for Image Caption Generation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[3] Chenxi Liu,et al. Attention Correctness in Neural Image Captioning , 2016, AAAI.
[4] Geoffrey E. Hinton,et al. Generating Text with Recurrent Neural Networks , 2011, ICML.
[5] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[6] Xirong Li,et al. Early Embedding and Late Reranking for Video Captioning , 2016, ACM Multimedia.
[7] Jiebo Luo,et al. Image Captioning with Semantic Attention , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[9] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[10] Wojciech Zaremba,et al. Recurrent Neural Network Regularization , 2014, ArXiv.
[11] Fei-Fei Li,et al. Deep visual-semantic alignments for generating image descriptions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Geoffrey E. Hinton,et al. Factored conditional restricted Boltzmann Machines for modeling motion style , 2009, ICML '09.
[13] Trevor Darrell,et al. Sequence to Sequence -- Video to Text , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[14] William B. Dolan,et al. Collecting Highly Parallel Data for Paraphrase Evaluation , 2011, ACL.
[15] Tianbao Yang,et al. Learning Attributes Equals Multi-Source Domain Generalization , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Zhe Gan,et al. Variational Autoencoder for Deep Learning of Images, Labels and Captions , 2016, NIPS.
[17] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[18] Trevor Darrell,et al. Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Xinlei Chen,et al. Mind's eye: A recurrent visual representation for image caption generation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Alon Lavie,et al. METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments , 2005, IEEvaluation@ACL.
[22] Wei Xu,et al. Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Marcus Rohrbach,et al. Translating Videos to Natural Language Using Deep Recurrent Neural Networks , 2014, NAACL.
[24] Ruslan Salakhutdinov,et al. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models , 2014, ArXiv.
[25] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[26] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[27] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[28] Trevor Darrell,et al. Long-term recurrent convolutional networks for visual recognition and description , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[30] Zhe Gan,et al. Adaptive Feature Abstraction for Translating Video to Text , 2018, AAAI.
[31] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[32] Tao Mei,et al. Jointly Modeling Embedding and Translation to Bridge Video and Language , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Geoffrey Zweig,et al. From captions to visual concepts and back , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Jian Sun,et al. Rich Image Captioning in the Wild , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[35] Chin-Yew Lin,et al. ROUGE: A Package for Automatic Evaluation of Summaries , 2004, ACL 2004.
[36] Xu Jia,et al. Guiding Long-Short Term Memory for Image Caption Generation , 2015, ArXiv.
[37] Xinlei Chen,et al. Microsoft COCO Captions: Data Collection and Evaluation Server , 2015, ArXiv.
[38] Zhe Gan,et al. Adaptive Feature Abstraction for Translating Video to Language , 2017, ICLR.
[39] Tao Mei,et al. MSR-VTT: A Large Video Description Dataset for Bridging Video and Language , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Ruslan Salakhutdinov,et al. A Multiplicative Model for Learning Distributed Text-Based Attribute Representations , 2014, NIPS.
[41] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[42] Christopher Joseph Pal,et al. Delving Deeper into Convolutional Networks for Learning Video Representations , 2015, ICLR.
[43] Zhe Gan,et al. StyleNet: Generating Attractive Visual Captions with Styles , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Ruslan Salakhutdinov,et al. Multimodal Neural Language Models , 2014, ICML.
[45] Wei Xu,et al. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN) , 2014, ICLR.
[46] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Chunhua Shen,et al. What Value Do Explicit High Level Concepts Have in Vision to Language Problems? , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Geoffrey E. Hinton,et al. Unsupervised Learning of Image Transformations , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[49] Quoc V. Le,et al. Grounded Compositional Semantics for Finding and Describing Images with Sentences , 2014, TACL.
[50] Geoffrey Zweig,et al. Language Models for Image Captioning: The Quirks and What Works , 2015, ACL.
[51] Changshui Zhang,et al. Aligning where to see and what to tell: image caption with region-based attention and scene factorization , 2015, ArXiv.
[52] U. Austin,et al. Translating Videos to Natural Language Using Deep Recurrent Neural Networks , 2017 .
[53] C. Lawrence Zitnick,et al. CIDEr: Consensus-based image description evaluation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[54] John Salvatier,et al. Theano: A Python framework for fast computation of mathematical expressions , 2016, ArXiv.
[55] Ye Yuan,et al. Review Networks for Caption Generation , 2016, NIPS.
[56] Peter Young,et al. From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions , 2014, TACL.
[57] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[58] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[59] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[60] Zhe Gan,et al. Factored Temporal Sigmoid Belief Networks for Sequence Learning , 2016, ICML.