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This paper presents a detailed study of improving visual representations for vision language (VL) tasks and develops an improved object detection model to provide object-centric representations of images.
Im2text: Describing images using 1 million captioned photographs
Vicente Ordonez, Girish Kulkarni, and Tamara L Berg · 2011
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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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From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Peter Young, Alice Lai, Micah Hodosh, and Julia Hockenmaier · 2014
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From captions to visual concepts and back
Hao Fang, Saurabh Gupta, Forrest Iandola, Rupesh K Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C Platt, et al · 2015
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Deep visual-semantic alignments for generating image descriptions
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Stacked attention networks for image question answering
Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, and Alex Smola · 2016
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Vse++: Improved visual-semantic embeddings
Fartash Faghri, David J Fleet, Jamie Ryan Kiros, and Sanja Fidler · 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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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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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Self-critical sequence training for image captioning
Steven J Rennie, Etienne Marcheret, Youssef Mroueh, Jerret Ross, and Vaibhava Goel · 2017
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Dual-path convolutional image-text embedding with instance loss
Zhedong Zheng, Liang Zheng, Michael Garrett, Yi Yang, and Yi-Dong Shen · 2017
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Bottom-up and top-down attention for image captioning and visual question answering
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang · 2018
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Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Tom Duerig, et al · 2018
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Stacked cross attention for image-text matching
Kuang-Huei Lee, Xi Chen, Gang Hua, Houdong Hu, and Xiaodong He · 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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A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi · 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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Meta module network for compositional visual reasoning
Wenhu Chen, Zhe Gan, Linjie Li, Yu Cheng, William Wang, and Jingjing Liu · 2019
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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
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LXMERT: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal · 2019
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Position focused attention network for image-text matching
Yaxiong Wang, Hao Yang, Xueming Qian, Lin Ma, Jing Lu, Biao Li, and Xin Fan · 2019
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CAMP: Cross-Modal adaptive message passing for text-image retrieval
Zihao Wang, Xihui Liu, Hongsheng Li, Lu Sheng, Junjie Yan, Xiaogang Wang, and Jing Shao · 2019
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Detectron2
Yuxin Wu, Alexander Kirillov, Francisco Massa, Wan-Yen Lo, and Ross Girshick · 2019
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Uniter: Learning universal image-text representations
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Attention on attention for image captioning
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Learning by abstraction: The neural state machine
Drew Hudson and Christopher D Manning · 2019
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GQA: A new dataset for real-world visual reasoning and compositional question answering
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VilBERT: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
Jiasen Lu, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
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Zhe Gan, Yen-Chun Chen, Linjie Li, Chen Zhu, Yu Cheng, and Jingjing Liu · 2020
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Vivo: Surpassing human performance in novel object captioning with visual vocabulary pre-training
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Pixel-bert: Aligning image pixels with text by deep multi-modal transformers
Zhicheng Huang, Zhaoyang Zeng, Bei Liu, Dongmei Fu, and Jianlong Fu · 2020
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In defense of grid features for visual question answering
Huaizu Jiang, Ishan Misra, Marcus Rohrbach, Erik Learned-Miller, and Xinlei Chen · 2020
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Oscar: Object-semantics aligned pre-training for vision-language tasks
Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiaowei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, Yejin Choi, and Jianfeng Gao · 2020
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Interbert: Vision-and-language interaction for multi-modal pretraining
Junyang Lin, An Yang, Yichang Zhang, Jie Liu, Jingren Zhou, and Hongxia Yang · 2020
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X-linear attention networks for image captioning
Yingwei Pan, Ting Yao, Yehao Li, and Tao Mei · 2020
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Fcos: A simple and strong anchor-free object detector
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2020
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Ernie-vil: Knowledge enhanced vision-language representations through scene graph
Fei Yu, Jiji Tang, Weichong Yin, Yu Sun, Hao Tian, Hua Wu, and Haifeng Wang · 2020
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Unified vision-language pre-training for image captioning and VQA
Luowei Zhou, Hamid Palangi, Lei Zhang, Houdong Hu, Jason J Corso, and Jianfeng Gao · 2020
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