Generating a description of an image is called image captioning.
Reading the bibliography…
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Building a semantically transparent corpus for the generation of referring expressions. In Proceedings of the Fourth International Natural Language Generation Conference . Association for Computational Linguistics, 130–132
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Meteor, m-bleu and m-ter: Evaluation metrics for high-correlation with human rankings of machine translation output. In Proceedings of the Third Workshop on Statistical Machine Translation . Association for Computational Linguistics, 115–118
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Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data . AcM, 1247–1250
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The use of spatial relations in referring expression generation. In Proceedings of the Fifth International Natural Language Generation Conference . Association for Computational Linguistics, 59–67
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Generating image descriptions using dependency relational patterns. In Proceedings of the 48th annual meeting of the association for computational linguistics . Association for Computational Linguistics, 1250–1258
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Every picture tells a story: Generating sentences from images. In European conference on computer vision . Springer, 15–29
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A game-theoretic approach to generating spatial descriptions. In Proceedings of the 2010 conference on empirical methods in natural language processing . Association for Computational Linguistics, 410–419
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Natural reference to objects in a visual domain. In Proceedings of the 6th international natural language generation conference . Association for Computational Linguistics, 95–104
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Learning photographic global tonal adjustment with a database of input/output image pairs. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on . IEEE, 97–104
Vladimir Bychkovsky, Sylvain Paris, Eric Chan, and Frédo Durand. 2011 · 2011
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Baby talk: Understanding and generating image descriptions. In Proceedings of the 24th CVPR . Citeseer
Girish Kulkarni, Visruth Premraj, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C Berg, and Tamara L Berg. 2011 · 2011
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Composing simple image descriptions using web-scale n-grams. In Proceedings of the Fifteenth Conference on Computational Natural Language Learning . Association for Computational Linguistics, 220–228
Siming Li, Girish Kulkarni, Tamara L Berg, Alexander C Berg, and Yejin Choi. 2011 · 2011
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Im2text: Describing images using 1 million captioned photographs. In Advances in Neural Information Processing Systems . 1143–1151
Vicente Ordonez, Girish Kulkarni, and Tamara L Berg. 2011 · 2011
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Learning to recognize daily actions using gaze. In European Conference on Computer Vision . Springer, 314–327
Alireza Fathi, Yin Li, and James M Rehg. 2012 · 2012
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Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems . 1097–1105
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
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Collective generation of natural image descriptions. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1 . Association for Computational Linguistics, 359–368
Polina Kuznetsova, Vicente Ordonez, Alexander C Berg, Tamara L Berg, and Yejin Choi. 2012 · 2012
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Active visual segmentation
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Midge: Generating image descriptions from computer vision detections. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics . Association for Computational Linguistics, 747–756
Margaret Mitchell, Xufeng Han, Jesse Dodge, Alyssa Mensch, Amit Goyal, Alex Berg, Kota Yamaguchi, Tamara Berg, Karl Stratos, and Hal Daumé III. 2012 · 2012
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Image description using visual dependency representations. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing . 1292–1302
Desmond Elliott and Frank Keller. 2013 · 2013
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Devise: A deep visual-semantic embedding model. In Advances in neural information processing systems . 2121–2129
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, and Tomas Mikolov. 2013 · 2013
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Framing image description as a ranking task: Data, models and evaluation metrics
Micah Hodosh, Peter Young, and Julia Hockenmaier. 2013 · 2013
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From where and how to what we see. In Proceedings of the IEEE International Conference on Computer Vision . 625–632
S Karthikeyan, Vignesh Jagadeesh, Renuka Shenoy, Miguel Ecksteinz, and BS Manjunath. 2013 · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
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Generating Expressions that Refer to Visible Objects.. In HLT-NAACL . 1174–1184
Margaret Mitchell, Kees Van Deemter, and Ehud Reiter. 2013 · 2013
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Exploring the role of gaze behavior and object detection in scene understanding
Kiwon Yun, Yifan Peng, Dimitris Samaras, Gregory J Zelinsky, and Tamara L Berg. 2013 · 2013
Cited alongside, same era.
Understanding scene understanding
Gregory J Zelinsky. 2013 · 2013
Cited alongside, same era.
On the properties of neural machine translation: Encoder-decoder approaches. In Association for Computational Linguistics . 103–111
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition . 580–587
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. 2014 · 2014
Cited alongside, same era.
Improving image-sentence embeddings using large weakly annotated photo collections. In European Conference on Computer Vision . Springer, 529–545
Yunchao Gong, Liwei Wang, Micah Hodosh, Julia Hockenmaier, and Svetlana Lazebnik. 2014 · 2014
Cited alongside, same era.
Generative adversarial nets. In Advances in neural information processing systems . 2672–2680
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Deep fragment embeddings for bidirectional image sentence mapping. In Advances in neural information processing systems . 1889–1897
Andrej Karpathy, Armand Joulin, and Fei Fei F Li. 2014 · 2014
Cited alongside, same era.
ReferItGame: Referring to Objects in Photographs of Natural Scenes.. In EMNLP . 787–798
Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, and Tamara L Berg. 2014 · 2014
Cited alongside, same era.
TREETALK: Composition and Compression of Trees for Image Descriptions
Polina Kuznetsova, Vicente Ordonez, Tamara L Berg, and Yejin Choi. 2014 · 2014
Cited alongside, same era.
Microsoft coco: Common objects in context. In European conference on computer vision . Springer, 740–755
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
Cited alongside, same era.
Explain images with multimodal recurrent neural networks
Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, and Alan L Yuille. 2014 · 2014
Cited alongside, same era.
Densecap: Fully convolutional localization networks for dense captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 4565–4574
Justin Johnson, Andrej Karpathy, and Li Fei-Fei. 2016 · 2016
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Exploring the limits of language modeling
Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, and Yonghui Wu. 2016 · 2016
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Multi-task sequence to sequence learning. In International Conference on Learning Representations (ICLR)
Minh-Thang Luong, Quoc V Le, Ilya Sutskever, Oriol Vinyals, and Lukasz Kaiser. 2016 · 2016
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Describing images by feeding LSTM with structural words. In Multimedia and Expo (ICME), 2016 IEEE International Conference on . IEEE, 1–6
Shubo Ma and Yahong Han. 2016 · 2016
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Generation and comprehension of unambiguous object descriptions. In Proceedings of the IEEE conference on computer vision and pattern recognition . 11–20
Junhua Mao, Jonathan Huang, Alexander Toshev, Oana Camburu, Alan L Yuille, and Kevin Murphy. 2016 · 2016
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SentiCap: Generating Image Descriptions with Sentiments.. In AAAI . 3574–3580
Alexander Patrick Mathews, Lexing Xie, and Xuming He. 2016 · 2016
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Sequence level training with recurrent neural networks. In International Conference on learning Representations (ICLR)
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
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Generative adversarial text to image synthesis. In Proceedings of Machine Learning Research , Vol. 48. 1060–1069
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. 2016 · 2016
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Joint image-text representation by gaussian visual-semantic embedding. In Proceedings of the 2016 ACM on Multimedia Conference . ACM, 207–211
Zhou Ren, Hailin Jin, Zhe Lin, Chen Fang, and Alan Yuille. 2016 · 2016
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Seeing with humans: Gaze-assisted neural image captioning
Yusuke Sugano and Andreas Bulling. 2016 · 2016
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Rich image captioning in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops . 49–56
Kenneth Tran, Xiaodong He, Lei Zhang, Jian Sun, Cornelia Carapcea, Chris Thrasher, Chris Buehler, and Chris Sienkiewicz. 2016 · 2016
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Conditional image generation with pixelcnn decoders. In Advances in Neural Information Processing Systems . 4790–4798
Aaron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
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Image captioning with deep bidirectional LSTMs. In Proceedings of the 2016 ACM on Multimedia Conference . ACM, 988–997
Cheng Wang, Haojin Yang, Christian Bartz, and Christoph Meinel. 2016b · 2016
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A parallel-fusion RNN-LSTM architecture for image caption generation. In Image Processing (ICIP), 2016 IEEE International Conference on . IEEE, 4448–4452
Minsi Wang, Li Song, Xiaokang Yang, and Chuanfei Luo. 2016a · 2016
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Encode, Review, and Decode: Reviewer Module for Caption Generation. In 30th Conference on Neural Image Processing System(NIPS)
Zhilin Yang Ye Yuan Yuexin Wu and Ruslan Salakhutdinov William W Cohen. 2016 · 2016
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Image captioning with semantic attention. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 4651–4659
Quanzeng You, Hailin Jin, Zhaowen Wang, Chen Fang, and Jiebo Luo. 2016 · 2016
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Bottom-up and top-down attention for image captioning and vqa
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang. 2017 · 2017
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Towards Diverse and Natural Image Descriptions via a Conditional GAN. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) . 2989–2998
Bo Dai, Dahua Lin, Raquel Urtasun, and Sanja Fidler. 2017 · 2017
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin. 2017 · 2017
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An empirical study of language cnn for image captioning. In Proceedings of the International Conference on Computer Vision (ICCV) . 1231–1240
Jiuxiang Gu, Gang Wang, Jianfei Cai, and Tsuhan Chen. 2017 · 2017
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Image-to-image translation with conditional adversarial networks. In Proceedings of the IEEE International Conference on Computer Vision (CVPR) . 5967–5976
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros. 2017 · 2017
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Categorical reparameterization with gumbel-softmax. In International Conference on Learning Representations (ICLR)
Eric Jang, Shixiang Gu, and Ben Poole. 2017 · 2017
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 2017
Later among the works it cites.
A survey of evolution of image captioning techniques
Akshi Kumar and Shivali Goel. 2017 · 2017
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Knowing when to look: Adaptive attention via A visual sentinel for image captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 3242–3250
Jiasen Lu, Caiming Xiong, Devi Parikh, and Richard Socher. 2017 · 2017
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The concrete distribution: A continuous relaxation of discrete random variables. In International Conference on Learning Representations (ICLR)
Chris J Maddison, Andriy Mnih, and Yee Whye Teh. 2017 · 2017
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Attend to You: Personalized Image Captioning with Context Sequence Memory Networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) . 6432–6440
Cesc Chunseong Park, Byeongchang Kim, and Gunhee Kim. 2017 · 2017
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Areas of Attention for Image Captioning. In Proceedings of the IEEE international conference on computer vision . 1251–1259
Marco Pedersoli, Thomas Lucas, Cordelia Schmid, and Jakob Verbeek. 2017 · 2017
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Deep Reinforcement Learning-based Image Captioning with Embedding Reward. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) . 1151–1159
Zhou Ren, Xiaoyu Wang, Ning Zhang, Xutao Lv, and Li-Jia Li. 2017 · 2017
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Self-critical sequence training for image captioning. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) . 1179–1195
Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jarret Ross, and Vaibhava Goel. 2017 · 2017
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Speaking the Same Language: Matching Machine to Human Captions by Adversarial Training. In IEEE International Conference on Computer Vision (ICCV) . 4155–4164
Rakshith Shetty, Marcus Rohrbach, Lisa Anne Hendricks, Mario Fritz, and Bernt Schiele. 2017 · 2017
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Paying Attention to Descriptions Generated by Image Captioning Models. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 2487–2496
Hamed R Tavakoli, Rakshith Shetty, Ali Borji, and Jorma Laaksonen. 2017 · 2017
Later among the works it cites.
Attention is all you need. In Advances in Neural Information Processing Systems . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Captioning images with diverse objects. In Proceedings of the IEEE conference on computer vision and pattern recognition . 1170–1178
Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond Mooney, Trevor Darrell, and Kate Saenko. 2017 · 2017
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Show and tell: Lessons learned from the 2015 mscoco image captioning challenge
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan. 2017 · 2017
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Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR) . 7378–7387
Yufei Wang, Zhe Lin, Xiaohui Shen, Scott Cohen, and Garrison W Cottrell. 2017 · 2017
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Incorporating copying mechanism in image captioning for learning novel objects. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE, 5263–5271
Ting Yao, Yingwei Pan, Yehao Li, and Tao Mei. 2017a · 2017
Later among the works it cites.
Sequence generative adversarial nets with policy gradient.. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence
Lantao Yu, Weinan Zhang, Jun Wang, and Yong Yu Seqgan. 2017 · 2017
Later among the works it cites.
Actor-critic sequence training for image captioning
Li Zhang, Flood Sung, Feng Liu, Tao Xiang, Shaogang Gong, Yongxin Yang, and Timothy M Hospedales. 2017 · 2017
Later among the works it cites.
Convolutional image captioning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 5561–5570
Jyoti Aneja, Aditya Deshpande, and Alexander G Schwing. 2018 · 2018
Closest in time.
A Survey on Automatic Image Caption Generation
Shuang Bai and Shan An. 2018 · 2018
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Text to Image Synthesis Using Generative Adversarial Networks
Cristian Bodnar. 2018 · 2018
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Maskgan: Better text generation via filling in the _
William Fedus, Ian Goodfellow, and Andrew M Dai. 2018 · 2018
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Learning-based Composite Metrics for Improved Caption Evaluation. In Proceedings of ACL 2018, Student Research Workshop . 14–20
Naeha Sharif, Lyndon White, Mohammed Bennamoun, and Syed Afaq Ali Shah. 2018 · 2018
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Text Generation Based on Generative Adversarial Nets with Latent Variables. In Pacific-Asia Conference on Knowledge Discovery and Data Mining . Springer, 92–103
Heng Wang, Zengchang Qin, and Tao Wan. 2018 · 2018
Closest in time.
CNN+ CNN: Convolutional Decoders for Image Captioning
Qingzhong Wang and Antoni B Chan. 2018 · 2018
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Image captioning and visual question answering based on attributes and external knowledge
Qi Wu, Chunhua Shen, Peng Wang, Anthony Dick, and Anton van den Hengel. 2018 · 2018
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Spatial transformer networks. In Advances in Neural Information Processing Systems . 2017–2025
Max Jaderberg, Karen Simonyan, Andrew Zisserman, et al · 2025
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Show, attend and tell: Neural image caption generation with visual attention. In International Conference on Machine Learning . 2048–2057
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio. 2015 · 2057
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