Mind's eye: A recurrent visual representation for image caption generation
暂无分享,去创建一个
[1] L. Lieberman,et al. Words versus Objects: Comparison of Free Verbal Recall , 1965, Psychological reports.
[2] Lukás Burget,et al. Strategies for training large scale neural network language models , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.
[3] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[4] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] C. Lawrence Zitnick,et al. Bringing Semantics into Focus Using Visual Abstraction , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[6] Frank Keller,et al. Comparing Automatic Evaluation Measures for Image Description , 2014, ACL.
[7] Karl Stratos,et al. Midge: Generating Image Descriptions From Computer Vision Detections , 2012, EACL.
[8] Xinlei Chen,et al. Learning a Recurrent Visual Representation for Image Caption Generation , 2014, ArXiv.
[9] Sharlene D. Newman,et al. Imagery in sentence comprehension: an fMRI study , 2004, NeuroImage.
[10] Quoc V. Le,et al. Grounded Compositional Semantics for Finding and Describing Images with Sentences , 2014, TACL.
[11] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[12] Fei-Fei Li,et al. Deep visual-semantic alignments for generating image descriptions , 2015, CVPR.
[13] Cyrus Rashtchian,et al. Every Picture Tells a Story: Generating Sentences from Images , 2010, ECCV.
[14] Alon Lavie,et al. METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments , 2005, IEEvaluation@ACL.
[15] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[16] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[17] Yejin Choi,et al. Baby talk: Understanding and generating simple image descriptions , 2011, CVPR 2011.
[18] 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).
[19] Svetlana Lazebnik,et al. Improving Image-Sentence Embeddings Using Large Weakly Annotated Photo Collections , 2014, ECCV.
[20] Fei-Fei Li,et al. ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[22] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[23] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[24] Marc'Aurelio Ranzato,et al. DeViSE: A Deep Visual-Semantic Embedding Model , 2013, NIPS.
[25] Liang Lin,et al. I2T: Image Parsing to Text Description , 2010, Proceedings of the IEEE.
[26] Yoshua Bengio,et al. Neural Probabilistic Language Models , 2006 .
[27] Geoffrey Zweig,et al. From captions to visual concepts and back , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[29] Geoffrey E. Hinton,et al. Generating Text with Recurrent Neural Networks , 2011, ICML.
[30] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[31] Wei Xu,et al. Explain Images with Multimodal Recurrent Neural Networks , 2014, ArXiv.
[32] A. Paivio,et al. Why are pictures easier to recall than words? , 1968 .
[33] Xinlei Chen,et al. Microsoft COCO Captions: Data Collection and Evaluation Server , 2015, ArXiv.
[34] Yejin Choi,et al. Collective Generation of Natural Image Descriptions , 2012, ACL.
[35] C. Lawrence Zitnick,et al. CIDEr: Consensus-based image description evaluation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[37] Armand Joulin,et al. Deep Fragment Embeddings for Bidirectional Image Sentence Mapping , 2014, NIPS.
[38] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[39] Cyrus Rashtchian,et al. Collecting Image Annotations Using Amazon’s Mechanical Turk , 2010, Mturk@HLT-NAACL.
[40] Geoffrey Zweig,et al. Context dependent recurrent neural network language model , 2012, 2012 IEEE Spoken Language Technology Workshop (SLT).
[41] Ruslan Salakhutdinov,et al. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models , 2014, ArXiv.
[42] Ruslan Salakhutdinov,et al. Multimodal Neural Language Models , 2014, ICML.
[43] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[44] Peter Young,et al. Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics , 2013, J. Artif. Intell. Res..
[45] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[46] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[47] Ronald J. Williams,et al. Experimental Analysis of the Real-time Recurrent Learning Algorithm , 1989 .
[48] Yiannis Aloimonos,et al. Corpus-Guided Sentence Generation of Natural Images , 2011, EMNLP.