Fetching the paper…
Reading the bibliography…
Large-scale video-language pre-training has made remarkable strides in advancing video-language understanding tasks.
Activitynet-qa: A dataset for understanding complex web videos via question answering
Zhou Yu, D. Xu, Jun Yu, Ting Yu, Zhou Zhao, Yueting Zhuang, and Dacheng Tao. 2019 · 1906
Earlier work this paper cites.
Least squares quantization in pcm
Stuart P. Lloyd. 1982 · 1982
Earlier work this paper cites.
Condensed movies: Story based retrieval with contextual embeddings
Max Bain, Arsha Nagrani, A. Brown, and Andrew Zisserman. 2020 · 2005
Earlier work this paper cites.
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. 2020 · 2010
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Localizing moments in video with natural language
Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, and Bryan C. Russell. 2017 · 2017
Earlier work this paper cites.
Dense-captioning events in videos
Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, and Juan Carlos Niebles. 2017 · 2017
Earlier work this paper cites.
Youtube-boundingboxes: A large high-precision human-annotated data set for object detection in video
Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, and Vincent Vanhoucke. 2017 · 2017
Earlier work this paper cites.
Learning a text-video embedding from incomplete and heterogeneous data
Antoine Miech, Ivan Laptev, and Josef Sivic. 2018 · 2018
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 · 2019
Earlier work this paper cites.
Cross-task weakly supervised learning from instructional videos
Dimitri Zhukov, Jean-Baptiste Alayrac, Ramazan Gokberk Cinbis, David F. Fouhey, Ivan Laptev, and Josef Sivic. 2019 · 2019
Earlier work this paper cites.
Power-bert: Accelerating bert inference via progressive word-vector elimination
Saurabh Goyal, Anamitra R. Choudhury, Saurabh Raje, Venkatesan T. Chakaravarthy, Yogish Sabharwal, and Ashish Verma. 2020 · 2020
Earlier work this paper cites.
Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick. 2020 · 2020
Earlier work this paper cites.
Dca: Diversified co-attention towards informative live video commenting
Zhihan Zhang, Zhiyi Yin, Shuhuai Ren, Xinhang Li, and Shicheng Li. 2020 · 2020
Earlier work this paper cites.
Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lucic, and Cordelia Schmid. 2021 · 2021
Earlier work this paper cites.
Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman. 2021 · 2021
Earlier work this paper cites.
Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani. 2021 · 2021
Earlier work this paper cites.
Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Soravit Changpinyo, Piyush Kumar Sharma, Nan Ding, and Radu Soricut. 2021 · 2021
Earlier work this paper cites.
Teachtext: Crossmodal generalized distillation for text-video retrieval
Ioana Croitoru, Simion-Vlad Bogolin, Yang Liu, Samuel Albanie, Marius Leordeanu, Hailin Jin, and Andrew Zisserman. 2021 · 2021
Earlier work this paper cites.
Violet : End-to-end video-language transformers with masked visual-token modeling
Tsu-Jui Fu, Linjie Li, Zhe Gan, Kevin Lin, William Yang Wang, Lijuan Wang, and Zicheng Liu. 2021 · 2021
Cited alongside, same era.
Less is more: Clipbert for video-and-language learning via sparse sampling
Jie Lei, Linjie Li, Luowei Zhou, Zhe Gan, Tamara L. Berg, Mohit Bansal, and Jingjing Liu. 2021 · 2021
Cited alongside, same era.
Clip4clip: An empirical study of clip for end to end video clip retrieval
Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, and Tianrui Li. 2021 · 2021
Cited alongside, same era.
Token pooling in vision transformers
Dmitrii Marin, Jen-Hao Rick Chang, Anurag Ranjan, Anish K. Prabhu, Mohammad Rastegari, and Oncel Tuzel. 2021 · 2021
Cited alongside, same era.
Queryd: A video dataset with high-quality text and audio narrations
Andreea-Maria Oncescu, João F. Henriques, Yang Liu, Andrew Zisserman, and Samuel Albanie. 2020 · 2021
X-pool: Cross-modal language-video attention for text-video retrieval
Satya Krishna Gorti, Noël Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, and Guangwei Yu. 2022 · 2022
Later among the works it cites.
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Doll’ar, and Ross B. Girshick. 2021 · 2022
Later among the works it cites.
Revealing single frame bias for video-and-language learning
Jie Lei, Tamara L. Berg, and Mohit Bansal. 2022 · 2022
Later among the works it cites.
Align and prompt: Video-and-language pre-training with entity prompts
Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, and Steven C. H. Hoi. 2021a · 2022
Later among the works it cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven C. H. Hoi. 2022 · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Spatiotemporal contrastive video representation learning
Rui Qian, Tianjian Meng, Boqing Gong, Ming-Hsuan Yang, Huisheng Wang, Serge Belongie, and Yin Cui. 2021 · 2021
Cited alongside, same era.
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, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021
Cited alongside, same era.
Dynamicvit: Efficient vision transformers with dynamic token sparsification
Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, and Cho-Jui Hsieh. 2021 · 2021
Cited alongside, same era.
Learning relation alignment for calibrated cross-modal retrieval
Shuhuai Ren, Junyang Lin, Guangxiang Zhao, Rui Men, An Yang, Jingren Zhou, Xu Sun, and Hongxia Yang. 2021 · 2021
Cited alongside, same era.
Tokenlearner: What can 8 learned tokens do for images and videos?
Michael S. Ryoo, A. J. Piergiovanni, Anurag Arnab, Mostafa Dehghani, and Anelia Angelova. 2021 · 2021
Cited alongside, same era.
Towards long-form video understanding
Chaoxia Wu and Philipp Krähenbühl. 2021 · 2021
Cited alongside, same era.
Videoclip: Contrastive pre-training for zero-shot video-text understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, and Florian Metze Luke Zettlemoyer Christoph Feichtenhofer. 2021 · 2021
Cited alongside, same era.
Mvitv2: Improved multiscale vision transformers for classification and detection
Yanghao Li, Chaoxia Wu, Haoqi Fan, Karttikeya Mangalam, Bo Xiong, Jitendra Malik, and Christoph Feichtenhofer. 2021c · 2022
Later among the works it cites.
Video swin transformer
Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, and Han Hu. 2021 · 2022
Later among the works it cites.
X-clip: End-to-end multi-grained contrastive learning for video-text retrieval
Yiwei Ma, Guohai Xu, Xiaoshuai Sun, Ming Yan, Ji Chao Zhang, and Rongrong Ji. 2022 · 2022
Later among the works it cites.
Long-form video-language pre-training with multimodal temporal contrastive learning
Yuchong Sun, Hongwei Xue, Ruihua Song, Bei Liu, Huan Yang, and Jianlong Fu. 2022 · 2022
Later among the works it cites.
Videomae: Masked autoencoders are data-efficient learners for self-supervised video pre-training
Zhan Tong, Yibing Song, Jue Wang, and Limin Wang. 2022 · 2022
Later among the works it cites.
Groupvit: Semantic segmentation emerges from text supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, and X. Wang. 2022 · 2022
Later among the works it cites.
Advancing high-resolution video-language representation with large-scale video transcriptions
Hongwei Xue, Tiankai Hang, Yanhong Zeng, Yuchong Sun, Bei Liu, Huan Yang, Jianlong Fu, and Baining Guo. 2021 · 2022
Later among the works it cites.
Clip-vip: Adapting pre-trained image-text model to video-language representation alignment
Hongwei Xue, Yuchong Sun, Bei Liu, Jianlong Fu, Rui Song, Houqiang Li, and Jiebo Luo. 2022 · 2022
Later among the works it cites.
Video-text modeling with zero-shot transfer from contrastive captioners
Shen Yan, Tao Zhu, Zirui Wang, Yuan Cao, Mi Zhang, Soham Ghosh, Yonghui Wu, and Jiahui Yu. 2022 · 2022
Later among the works it cites.
Hitea: Hierarchical temporal-aware video-language pre-training
Qinghao Ye, Guohai Xu, Ming Yan, Haiyang Xu, Qi Qian, Ji Chao Zhang, and Fei Huang. 2022 · 2022
Later among the works it cites.
Pumer: Pruning and merging tokens for efficient vision language models
Qingqing Cao, Bhargavi Paranjape, and Hanna Hajishirzi. 2023 · 2023
Closest in time.
Delving into the openness of CLIP
Shuhuai Ren, Lei Li, Xuancheng Ren, Guangxiang Zhao, and Xu Sun. 2023a · 2023
Closest in time.
Crossget: Cross-guided ensemble of tokens for accelerating vision-language transformers
Dachuan Shi, Chaofan Tao, Anyi Rao, Zhendong Yang, Chun Yuan, and Jiaqi Wang. 2023 · 2023
Closest in time.