Object Hallucination in Image Captioning

Long short-term memory

Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997

Earlier work this paper cites.

Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Satanjeev Banerjee and Alon Lavie. 2005 · 2005

Earlier work this paper cites.

Microsoft coco: Common objects in context

Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014

Earlier work this paper cites.

Microsoft coco captions: Data collection and evaluation server

Original

Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick. 2015 · 2015

Earlier work this paper cites.

Long-term recurrent convolutional networks for visual recognition and description

Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell. 2015 · 2015

Earlier work this paper cites.

Deep visual-semantic alignments for generating image descriptions

Andrej Karpathy and Li Fei-Fei. 2015 · 2015

Earlier work this paper cites.

Cider: Consensus-based image description evaluation

Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015

Earlier work this paper cites.

Spice: Semantic propositional image caption evaluation

Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould. 2016 · 2016

Cited alongside, same era.

Deep residual learning for image recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016

Cited alongside, same era.

Deep compositional captioning: Describing novel object categories without paired training data

Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond Mooney, Kate Saenko, and Trevor Darrell. 2016 · 2016

Cited alongside, same era.

Re-evaluating automatic metrics for image captioning

Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, and Erkut Erdem. 2016 · 2016

Cited alongside, same era.

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 · 2017

Cited alongside, same era.

The Joint Video and Language Understanding Workshop: MovieQA and The Large Scale Movie Description Challenge (LSMDC)

Anna Rohrbach, Makarand Tapaswi, Atousa Torabi, Tegan Maharaj, Marcus Rohrbach, Sanja Fidler Christopher Pal, and Bernt Schiele. 2017a · 2017

Later among the works it cites.

Speaking the same language: Matching machine to human captions by adversarial training

Rakshith Shetty, Marcus Rohrbach, Lisa Anne Hendricks, Mario Fritz, and Bernt Schiele. 2017 · 2017

Later among the works it cites.

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. 2018 · 2018

Closest in time.

Learning to evaluate image captioning

Yin Cui, Guandao Yang, Andreas Veit, Xun Huang, and Serge Belongie. 2018 · 2018

Closest in time.

Neural baby talk

Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh. 2018 · 2018

Closest in time.

Discriminability objective for training descriptive captions