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Image captioning is conventionally formulated as the task of generating captions for images that match the distribution of reference image-caption pairs.
Approche mixte pour l’extraction automatique de terminologie: statistiques lexicales et filtres linguistiques
Béatrice Daille · 1994
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BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Novel dataset for fine-grained image categorization
Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao, and Li Fei-Fei · 2011
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Framing image description as a ranking task: Data, models and evaluation metrics
Micah Hodosh, Peter Young, and Julia Hockenmaier · 2013
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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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Language models for image captioning: The quirks and what works
Jacob Devlin, Hao Cheng, Hao Fang, Saurabh Gupta, Li Deng, Xiaodong He, Geoffrey Zweig, and Margaret Mitchell · 2015
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Fei-Fei Li · 2015
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CIDEr: Consensus-based image description evaluation
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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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Dense captioning with joint inference and visual context
Linjie Yang, Kevin Tang, Jianchao Yang, and Li-Jia Li · 2017
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Generating diverse and meaningful captions
Annika Lindh, Robert J Ross, Abhijit Mahalunkar, Giancarlo Salton, and John D Kelleher · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut · 2018
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nocaps: novel object captioning at scale
Harsh Agrawal, Karan Desai, Yufei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, and Peter Anderson · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Connecting vision and language with localized narratives
Jordi Pont-Tuset, Jasper Uijlings, Soravit Changpinyo, Radu Soricut, and Vittorio Ferrari · 2020
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CLIPScore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Unifying multimodal transformer for bi-directional image and text generation
Yupan Huang, Hongwei Xue, Bei Liu, and Yutong Lu · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Bidimensional leaderboards: Generate and evaluate language hand in hand
Decap: Decoding clip latents for zero-shot captioning
Wei Li, Linchao Zhu, Longyin Wen, and Yi Yang · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob Mcgrew, Ilya Sutskever, and Mark Chen · 2022
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Text-only training for image captioning using noise-injected clip
David Nukrai, Ron Mokady, and Amir Globerson · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Lavinia Dunagan, Jacob Morrison, Alexander R Fabbri, Yejin Choi, and Noah A Smith · 2021
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Transparent human evaluation for image captioning
Jungo Kasai, Keisuke Sakaguchi, Lavinia Dunagan, Jacob Morrison, Ronan Le Bras, Yejin Choi, and Noah A Smith · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Primer: Searching for efficient transformers for language modeling
David R So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, and Quoc V Le · 2021
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Vinvl: Revisiting visual representations in vision-language models
Pengchuan Zhang, Xiujun Li, Xiaowei Hu, Jianwei Yang, Lei Zhang, Lijuan Wang, Yejin Choi, and Jianfeng Gao · 2021
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Cm3: A causal masked multimodal model of the internet
Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin, Hu Xu, Naman Goyal, Dmytro Okhonko, Mandar Joshi, Gargi Ghosh, Mike Lewis, et al · 2022
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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Language models can see: plugging visual controls in text generation
Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lingpeng Kong, and Nigel Collier · 2022
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Zerocap: Zero-shot image-to-text generation for visual-semantic arithmetic
Yoad Tewel, Yoav Shalev, Idan Schwartz, and Lior Wolf · 2022
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Clip-diffusion-lm: Apply diffusion model on image captioning
Shitong Xu · 2022
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Coca: Contrastive captioners are image-text foundation models
Jiahui Yu, Zirui Wang, Vijay Vasudevan, Legg Yeung, Mojtaba Seyedhosseini, and Yonghui Wu · 2022
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
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Scaling vision transformers
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer · 2022
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Distincive image captioning via clip guided group optimization
Youyuan Zhang, Jiuniu Wang, Hao Wu, and Wenjia Xu · 2022
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Exploring discrete diffusion models for image captioning
Zixin Zhu, Yixuan Wei, Jianfeng Wang, Zhe Gan, Zheng Zhang, Le Wang, Gang Hua, Lijuan Wang, Zicheng Liu, and Han Hu · 2022
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i c 3 ic^{3} : Image captioning by committee consensus
David M Chan, Austin Myers, Sudheendra Vijayanarasimhan, David A Ross, and John Canny · 2023
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Stay on topic with classifier-free guidance
Guillaume Sanchez, Honglu Fan, Alexander Spangher, Elad Levi, Pawan Sasanka Ammanamanchi, and Stella Biderman · 2023
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Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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