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Contrastive learning-based vision-language pre-training approaches, such as CLIP, have demonstrated great success in many vision-language tasks.
Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
Li Fei-Fei, Rob Fergus, and Pietro Perona · 2004
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Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Sun database: Large-scale scene recognition from abbey to zoo
Jianxiong Xiao, James Hays, Krista A Ehinger, Aude Oliva, and Antonio Torralba · 2010
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Cats and dogs
Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman, and CV Jawahar · 2012
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Fine-grained visual classification of aircraft
Subhransu Maji, Esa Rahtu, Juho Kannala, Matthew Blaschko, and Andrea Vedaldi · 2013
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Food-101–mining discriminative components with random forests
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool · 2014
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Describing textures in the wild
Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Sammy Mohamed, and Andrea Vedaldi · 2014
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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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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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Multimodal task-driven dictionary learning for image classification
Soheil Bahrampour, Nasser M Nasrabadi, Asok Ray, and William Kenneth Jenkins · 2015
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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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From softmax to sparsemax: A sparse model of attention and multi-label classification
Andre Martins and Ramon Astudillo · 2016
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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You type a few words and we do the rest: Image recommendation for social multimedia posts
Tianlang Chen, Yuxiao Chen, Han Guo, and Jiebo Luo · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Convolutional dictionary learning: A comparative review and new algorithms
Cristina Garcia-Cardona and Brendt Wohlberg · 2018
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Learning semantic concepts and order for image and sentence matching
Yan Huang, Qi Wu, Chunfeng Song, and Liang Wang · 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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Yufeng Cui, Lichen Zhao, Feng Liang, Yangguang Li, and Jing Shao · 2022
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An empirical study of training end-to-end vision-and-language transformers
Zi-Yi Dou, Yichong Xu, Zhe Gan, Jianfeng Wang, Shuohang Wang, Lijuan Wang, Chenguang Zhu, Pengchuan Zhang, Lu Yuan, Nanyun Peng, et al · 2022
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Multi-modal convolutional dictionary learning
Fangyuan Gao, Xin Deng, Mai Xu, Jingyi Xu, and Pier Luigi Dragotti · 2022
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Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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Unimo-2: End-to-end unified vision-language grounded learning
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Deep vit features as dense visual descriptors
Shir Amir, Yossi Gandelsman, Shai Bagon, and Tali Dekel · 2021
Cited alongside, same era.
Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding, and Radu Soricut · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Cited alongside, same era.
Clip-adapter: Better vision-language models with feature adapters
Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, and Yu Qiao · 2021
Cited alongside, same era.
Seeing out of the box: End-to-end pre-training for vision-language representation learning
Zhicheng Huang, Zhaoyang Zeng, Yupan Huang, Bei Liu, Dongmei Fu, and Jianlong Fu · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Wei Li, Can Gao, Guocheng Niu, Xinyan Xiao, Hao Liu, Jiachen Liu, Hua Wu, and Haifeng Wang · 2022
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Frozen clip models are efficient video learners
Ziyi Lin, Shijie Geng, Renrui Zhang, Peng Gao, Gerard de Melo, Xiaogang Wang, Jifeng Dai, Yu Qiao, and Hongsheng Li · 2022
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Beit v2: Masked image modeling with vector-quantized visual tokenizers
Zhiliang Peng, Li Dong, Hangbo Bao, Qixiang Ye, and Furu Wei · 2022
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Learning granularity-unified representations for text-to-image person re-identification
Zhiyin Shao, Xinyu Zhang, Meng Fang, Zhifeng Lin, Jian Wang, and Changxing Ding · 2022
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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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Image as a foreign language: Beit pretraining for all vision and vision-language tasks
Wenhui Wang, Hangbo Bao, Li Dong, Johan Bjorck, Zhiliang Peng, Qiang Liu, Kriti Aggarwal, Owais Khan Mohammed, Saksham Singhal, Subhojit Som, et al · 2022
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Vision-language pre-training with triple contrastive learning
Jinyu Yang, Jiali Duan, Son Tran, Yi Xu, Sampath Chanda, Liqun Chen, Belinda Zeng, Trishul Chilimbi, and Junzhou Huang · 2022
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Vision-language pre-training with triple contrastive learning
Jinyu Yang, Jiali Duan, Son Tran, Yi Xu, Sampath Chanda, Liqun Chen, Belinda Zeng, Trishul Chilimbi, and Junzhou Huang · 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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Sine: Single image editing with text-to-image diffusion models
Zhixing Zhang, Ligong Han, Arnab Ghosh, Dimitris Metaxas, and Jian Ren · 2022
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More than just attention: Improving cross-modal attentions with contrastive constraints for image-text matching
Yuxiao Chen, Jianbo Yuan, Long Zhao, Tianlang Chen, Rui Luo, Larry Davis, and Dimitris N Metaxas · 2023
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HiCLIP: Contrastive language-image pretraining with hierarchy-aware attention
Shijie Geng, Jianbo Yuan, Yu Tian, Yuxiao Chen, and Yongfeng Zhang · 2023
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Prompt, generate, then cache: Cascade of foundation models makes strong few-shot learners
Renrui Zhang, Xiangfei Hu, Bohao Li, Siyuan Huang, Hanqiu Deng, Hongsheng Li, Yu Qiao, and Peng Gao · 2023
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Learning 3d representations from 2d pre-trained models via image-to-point masked autoencoders
Renrui Zhang, Liuhui Wang, Yu Qiao, Peng Gao, and Hongsheng Li · 2023
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Parameter is not all you need: Starting from non-parametric networks for 3d point cloud analysis
Renrui Zhang, Liuhui Wang, Yali Wang, Peng Gao, Hongsheng Li, and Jianbo Shi · 2023
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