Fetching the paper…
Reading the bibliography…
Pre-Trained Vision-Language Models (VL-PTMs) have shown promising capabilities in grounding natural language in image data, facilitating a broad variety of cross-modal tasks.
Understanding natural language commands for robotic navigation and mobile manipulation
Stefanie Tellex, Thomas Kollar, Steven Dickerson, Matthew Walter, Ashis Banerjee, Seth Teller, and Nicholas Roy · 2011
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.
Image retrieval using scene graphs
Justin Johnson, Ranjay Krishna, Michael Stark, Li-Jia Li, David Shamma, Michael Bernstein, and Li Fei-Fei · 2015
Earlier work this paper cites.
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei · 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.
Deep learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Generation and comprehension of unambiguous object descriptions
Junhua Mao, Jonathan Huang, Alexander Toshev, Oana Camburu, Alan L Yuille, and Kevin Murphy · 2016
Earlier work this paper cites.
Grounding of textual phrases in images by reconstruction
Anna Rohrbach, Marcus Rohrbach, Ronghang Hu, Trevor Darrell, and Bernt Schiele · 2016
Earlier work this paper cites.
Modeling context in referring expressions
Licheng Yu, Patrick Poirson, Shan Yang, Alexander C Berg, and Tamara L Berg · 2016
Earlier work this paper cites.
Visual dialog
Abhishek Das, Satwik Kottur, Khushi Gupta, Avi Singh, Deshraj Yadav, José MF Moura, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Scene graph generation by iterative message passing
Danfei Xu, Yuke Zhu, Christopher B Choy, and Li Fei-Fei · 2017
Earlier work this paper cites.
A survey on deep learning-based fine-grained object classification and semantic segmentation
Bo Zhao, Jiashi Feng, Xiao Wu, and Shuicheng Yan · 2017
Earlier work this paper cites.
MAttNet: Modular attention network for referring expression comprehension
Licheng Yu, Zhe Lin, Xiaohui Shen, Jimei Yang, Xin Lu, Mohit Bansal, and Tamara L Berg · 2018
Earlier work this paper cites.
Neural motifs: Scene graph parsing with global context
Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi · 2018
Cited alongside, same era.
Grounding referring expressions in images by variational context
Hanwang Zhang, Yulei Niu, and Shih-Fu Chang · 2018
Cited alongside, same era.
Knowledge-embedded routing network for scene graph generation
Tianshui Chen, Weihao Yu, Riquan Chen, and Liang Lin · 2019
Cited alongside, same era.
Learning by abstraction: The neural state machine
Drew A. Hudson and Christopher D. Manning · 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.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller · 2019
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, et al · 2020
Later among the works it cites.
Eliciting knowledge from language models using automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh · 2020
Later among the works it cites.
Pcpl: Predicate-correlation perception learning for unbiased scene graph generation
Shaotian Yan, Chen Shen, Zhongming Jin, Jianqiang Huang, Rongxin Jiang, Yaowu Chen, and Xian-Sheng Hua · 2020
Later among the works it cites.
Unifying vision-and-language tasks via text generation
Jaemin Cho, Jie Lei, Hao Tan, and Mohit Bansal · 2021
Closest in time.
Learning of visual relations: The devil is in the tails
Alakh Desai, Tz-Ying Wu, Subarna Tripathi, and Nuno Vasconcelos · 2021
Closest in time.
Making pre-trained language models better few-shot learners
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2019
Cited alongside, same era.
Zero-shot grounding of objects from natural language queries
Arka Sadhu, Kan Chen, and Ram Nevatia · 2019
Cited alongside, same era.
Explainable and explicit visual reasoning over scene graphs
Jiaxin Shi, Hanwang Zhang, and Juanzi Li · 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.
LXMERT: Learning cross-modality encoder representations from transformers
Hao Tan and Mohit Bansal · 2019
Cited alongside, same era.
Learning to compose dynamic tree structures for visual contexts
Kaihua Tang, Hanwang Zhang, Baoyuan Wu, Wenhan Luo, and Wei Liu · 2019
Cited alongside, same era.
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
Closest in time.
Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
Closest in time.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2021
Closest in time.
Learning how to ask: Querying LMs with mixtures of soft prompts
Guanghui Qin and Jason Eisner · 2021
Closest in time.
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
Closest in time.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Closest in time.
Measuring social biases in grounded vision and language embeddings
Candace Ross, Boris Katz, and Andrei Barbu · 2021
Closest in time.
Multimodal few-shot learning with frozen language models
Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, SM Eslami, Oriol Vinyals, and Felix Hill · 2021
Closest in time.
SimVLM: Simple visual language model pretraining with weak supervision
Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, and Yuan Cao · 2021
Closest in time.
ERNIE-ViL: Knowledge enhanced vision-language representations through scene graphs
Fei Yu, Jiji Tang, Weichong Yin, Yu Sun, Hao Tian, Hua Wu, and Haifeng Wang · 2021
Closest in time.
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
Closest in time.
Calibrate before use: Improving few-shot performance of language models
Tony Z Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh · 2021
Closest in time.
Learning to prompt for vision-language models
Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu · 2021
Closest in time.