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Vision-language pre-training (VLP) has recently proven highly effective for various uni- and multi-modal downstream applications.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie · 2005
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
Referitgame: Referring to objects in photographs of natural scenes
Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, and Tamara Berg · 2014
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
Earlier work this paper cites.
Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
Earlier work this paper cites.
Learning both weights and connections for efficient neural network
Song Han, Jeff Pool, John Tran, and William Dally · 2015
Earlier work this paper cites.
Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Bryan A Plummer, Liwei Wang, Chris M Cervantes, Juan C Caicedo, Julia Hockenmaier, and Svetlana Lazebnik · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Spice: Semantic propositional image caption evaluation
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Gromov-wasserstein averaging of kernel and distance matrices
Gabriel Peyré, Marco Cuturi, and Justin Solomon · 2016
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Modeling context in referring expressions
Licheng Yu, Patrick Poirson, Shan Yang, Alexander C Berg, and Tamara L Berg · 2016
Earlier work this paper cites.
Accurate, large minibatch sgd: Training imagenet in 1 hour
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, and Kaiming He · 2017
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 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
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Large batch training of convolutional networks
Yang You, Igor Gitman, and Boris Ginsburg · 2017
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Cascade r-cnn: Delving into high quality object detection
Zhaowei Cai and Nuno Vasconcelos · 2018
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Learning generative models with sinkhorn divergences
Aude Genevay, Gabriel Peyré, and Marco Cuturi · 2018
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Sobolev gan
Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, and Yu Cheng · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Normalized wasserstein for mixture distributions with applications in adversarial learning and domain adaptation
Yogesh Balaji, Rama Chellappa, and Soheil Feizi · 2019
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Improving sequence-to-sequence learning via optimal transport
Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, and Lawrence Carin · 2019
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Earlier work this paper cites.
Lvis: A dataset for large vocabulary instance segmentation
Agrim Gupta, Piotr Dollar, and Ross Girshick · 2019
Cited alongside, same era.
Supervised multimodal bitransformers for classifying images and text
Douwe Kiela, Suvrat Bhooshan, Hamed Firooz, and Davide Testuggine · 2019
Cited alongside, same era.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
Cited alongside, same era.
Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
Cited alongside, same era.
Sobolev descent
Youssef Mroueh, Tom Sercu, and Anant Raj · 2019
Cited alongside, same era.
Mdetr-modulated detection for end-to-end multi-modal understanding
Aishwarya Kamath, Mannat Singh, Yann LeCun, Gabriel Synnaeve, Ishan Misra, and Nicolas Carion · 2021
Later among the works it cites.
Vilt: Vision-and-language transformer without convolution or region supervision
Wonjae Kim, Bokyung Son, and Ildoo Kim · 2021
Later among the works it cites.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Later among the works it cites.
Slip: Self-supervision meets language-image pre-training
Norman Mu, Alexander Kirillov, David A. Wagner, and Saining Xie · 2021
Later among the works it cites.
Text generation by learning from demonstrations
Richard Yuanzhe Pang and He He · 2021
Later among the works it cites.
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Computational optimal transport: With applications to data science
Gabriel Peyré, Marco Cuturi, et al · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
Cited alongside, same era.
Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai · 2019
Cited alongside, same era.
A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi · 2019
Cited alongside, same era.
Lxmert: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal · 2019
Cited alongside, same era.
Eda: Easy data augmentation techniques for boosting performance on text classification tasks
Jason Wei and Kai Zou · 2019
Cited alongside, same era.
Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
Cited alongside, same era.
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Probing inter-modality: Visual parsing with self-attention for vision-and-language pre-training
Hongwei Xue, Yupan Huang, Bei Liu, Houwen Peng, Jianlong Fu, Houqiang Li, and Jiebo Luo · 2021
Later among the works it cites.
Multimodal contrastive training for visual representation learning
Xin Yuan, Zhe Lin, Jason Kuen, Jianming Zhang, Yilin Wang, Michael Maire, Ajinkya Kale, and Baldo Faieta · 2021
Later among the works it cites.
Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
Later among the works it cites.
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
Later among the works it cites.
Masked siamese networks for label-efficient learning
Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, and Nicolas Ballas · 2022
Closest in time.
Vicreg: Variance-invariance-covariance regularization for self-supervised learning
Adrien Bardes, Jean Ponce, and Yann LeCun · 2022
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On the duality between contrastive and non-contrastive self-supervised learning
Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, and Yann Lecun · 2022
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Multimodal masked autoencoders learn transferable representations
Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurams, Sergey Levine, and P. Abbeel · 2022
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
Closest in time.
Cmal: A novel cross-modal associative learning framework for vision-language pre-training
Zhiyuan Ma, Jianjun Li, Guohui Li, and Kaiyan Huang · 2022
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Multimodal learning using optimal transport for sarcasm and humor detection
Shraman Pramanick, Aniket Roy, and Vishal M Patel · 2022
Closest in time.
Max-margin contrastive learning
Anshul Shah, Suvrit Sra, Rama Chellappa, and Anoop Cherian · 2022
Closest in time.
Flava: A foundational language and vision alignment model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela · 2022
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Filip: Fine-grained interactive language-image pre-training
Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, and Chunjing Xu · 2022
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Learning visual representation from modality-shared contrastive language-image pre-training
Haoxuan You, Luowei Zhou, Bin Xiao, Noel Codella, Yu Cheng, Ruochen Xu, Shih-Fu Chang, and Lu Yuan · 2022
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Multi-grained vision language pre-training: Aligning texts with visual concepts
Yan Zeng, Xinsong Zhang, and Hang Li · 2022
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Glipv2: Unifying localization and vision-language understanding
Haotian Zhang, Pengchuan Zhang, Xiaowei Hu, Yen-Chun Chen, Liunian Harold Li, Xiyang Dai, Lijuan Wang, Lu Yuan, Jenq-Neng Hwang, and Jianfeng Gao · 2022
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Fame-vil: Multi-tasking vision-language model for heterogeneous fashion tasks
Xiao Han, Xiatian Zhu, Licheng Yu, Li Zhang, Yi-Zhe Song, and Tao Xiang · 2023
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Unifying vision-language representation space with single-tower transformer
Jiho Jang, Chaerin Kong, Donghyeon Jeon, Seonhoon Kim, and Nojun Kwak · 2023
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Multi-modal representation learning with text-driven soft masks
Jaeyoo Park and Bohyung Han · 2023
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Egovlpv2: Egocentric video-language pre-training with fusion in the backbone
Shraman Pramanick, Yale Song, Sayan Nag, Kevin Qinghong Lin, Hardik Shah, Mike Zheng Shou, Rama Chellappa, and Pengchuan Zhang · 2023
Closest in time.