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Explaining an image with missing or non-existent objects is known as object bias (hallucination) in image captioning.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
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The unreasonable effectiveness of data
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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
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Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadarrama, Marcus Rohrbach, Subhashini Venugopalan, Kate Saenko, and Trevor Darrell · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2015
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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 Zemel, and Yoshua Bengio · 2015
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Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalanditis, Li-Jia Li, David A Shamma, Michael Bernstein, and Li Fei-Fei · 2016
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Neural baby talk
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Object hallucination in image captioning
Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, and Kate Saenko · 2018
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Good news, everyone! context driven entity-aware captioning for news images
Ali Furkan Biten, Lluis Gomez, Marçal Rusinol, and Dimosthenis Karatzas · 2019
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Show, control and tell: A framework for generating controllable and grounded captions
Marcella Cornia, Lorenzo Baraldi, and Rita Cucchiara · 2019
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Attention on attention for image captioning
Lun Huang, Wenmin Wang, Jie Chen, and Xiao-Yong Wei · 2019
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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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
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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2017
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Deep Visual-Semantic Alignments for Generating Image Descriptions
Andrej Karpathy and Li Fei-Fei · 2017
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Understanding blind people’s experiences with computer-generated captions of social media images
Haley MacLeod, Cynthia L Bennett, Meredith Ringel Morris, and Edward Cutrell · 2017
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Self-critical sequence training for image captioning
Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jarret Ross, and Vaibhava Goel · 2017
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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
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Towards causal vqa: Revealing and reducing spurious correlations by invariant and covariant semantic editing
Vedika Agarwal, Rakshith Shetty, and Mario Fritz · 2020
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Say as you wish: Fine-grained control of image caption generation with abstract scene graphs
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Shortcut learning in deep neural networks
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis, Richard Zemel, Wieland Brendel, Matthias Bethge, and Felix A Wichmann · 2020
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Transform and tell: Entity-aware news image captioning
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Towards unique and informative captioning of images
Zeyu Wang, Berthy Feng, Karthik Narasimhan, and Olga Russakovsky · 2020
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Deconfounded image captioning: A causal retrospect
Xu Yang, Hanwang Zhang, and Jianfei Cai · 2020
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Comprehensive image captioning via scene graph decomposition
Yiwu Zhong, Liwei Wang, Jianshu Chen, Dong Yu, and Yin Li · 2020
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Towards accurate text-based image captioning with content diversity exploration
Guanghui Xu, Shuaicheng Niu, Mingkui Tan, Yucheng Luo, Qing Du, and Qi Wu · 2021
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