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Video-text retrieval plays an essential role in multi-modal research and has been widely used in many real-world web applications.
Use what you have: Video retrieval using representations from collaborative experts
Yang Liu, Samuel Albanie, Arsha Nagrani, and Andrew Zisserman. 2019 · 1907
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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Learning precise timing with lstm recurrent networks
Felix A Gers, Nicol N Schraudolph, and Jürgen Schmidhuber. 2002 · 2002
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UniVL: A unified video and language pre-training model for multimodal understanding and generation
Huaishao Luo, Lei Ji, Botian Shi, Haoyang Huang, Nan Duan, Tianrui Li, Jason Li, Taroon Bharti, and Ming Zhou. 2020 · 2002
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HERO: Hierarchical encoder for video+ language omni-representation pre-training
Linjie Li, Yen-Chun Chen, Yu Cheng, Zhe Gan, Licheng Yu, and Jingjing Liu. 2020 · 2005
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Avlnet: Learning audio-visual language representations from instructional videos
Andrew Rouditchenko, Angie Boggust, David Harwath, Dhiraj Joshi, Samuel Thomas, Kartik Audhkhasi, Rogerio Feris, Brian Kingsbury, Michael Picheny, Antonio Torralba, et al. 2020 · 2006
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Collecting highly parallel data for paraphrase evaluation
David Chen and William Dolan. 2011 · 2011
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Unifying visual-semantic embeddings with multimodal neural language models
Ryan Kiros, Ruslan Salakhutdinov, and Richard S Zemel. 2014 · 2014
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2015 · 2015
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The long-short story of movie description
Anna Rohrbach, Marcus Rohrbach, and Bernt Schiele. 2015 · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri. 2015 · 2015
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Translating videos to natural language using deep recurrent neural networks
Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond J. Mooney, and Kate Saenko. 2015 · 2015
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Learning language-visual embedding for movie understanding with natural-language
Atousa Torabi, Niket Tandon, and Leonid Sigal. 2016 · 2016
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Msr-vtt: A large video description dataset for bridging video and language
Jun Xu, Tao Mei, Ting Yao, and Yong Rui. 2016 · 2016
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Localizing moments in video with natural language
Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, and Bryan Russell. 2017 · 2017
Cited alongside, same era.
Temporal tessellation: A unified approach for video analysis
Dotan Kaufman, Gil Levi, Tal Hassner, and Lior Wolf. 2017 · 2017
Cited alongside, same era.
SGDR: stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
End-to-end concept word detection for video captioning, retrieval, and question answering
Youngjae Yu, Hyungjin Ko, Jongwook Choi, and Gunhee Kim. 2017 · 2017
Cited alongside, same era.
Multi-modal transformer for video retrieval
Valentin Gabeur, Chen Sun, Karteek Alahari, and Cordelia Schmid. 2020 · 2020
Later among the works it cites.
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Antoine Miech, Jean-Baptiste Alayrac, Lucas Smaira, Ivan Laptev, Josef Sivic, and Andrew Zisserman. 2020 · 2020
Later among the works it cites.
Actbert: Learning global-local video-text representations
Linchao Zhu and Yi Yang. 2020 · 2020
Later among the works it cites.
Noise estimation using density estimation for self-supervised multimodal learning
Elad Amrani, Rami Ben-Ari, Daniel Rotman, and Alex Bronstein. 2021 · 2021
Closest in time.
Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid. 2021 · 2021
Closest in time.
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Abien Fred Agarap. 2018 · 2018
Cited alongside, same era.
Learning joint embedding with multimodal cues for cross-modal video-text retrieval
Niluthpol Chowdhury Mithun, Juncheng Li, Florian Metze, and Amit K Roy-Chowdhury. 2018 · 2018
Cited alongside, same era.
Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Piyush Sharma, Nan Ding, Sebastian Goodman, and Radu Soricut. 2018 · 2018
Cited alongside, same era.
Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy. 2018 · 2018
Cited alongside, same era.
A joint sequence fusion model for video question answering and retrieval
Youngjae Yu, Jongseok Kim, and Gunhee Kim. 2018 · 2018
Cited alongside, same era.
Cross-modal and hierarchical modeling of video and text
Bowen Zhang, Hexiang Hu, and Fei Sha. 2018 · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman. 2021 · 2021
Closest in time.
Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani. 2021 · 2021
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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
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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 · 2021
Closest in time.
Mdmmt: Multidomain multimodal transformer for video retrieval
Maksim Dzabraev, Maksim Kalashnikov, Stepan Komkov, and Aleksandr Petiushko. 2021 · 2021
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Less is more: Clipbert for video-and-language learningvia sparse sampling
Jie Lei, Linjie Li, Luowei Zhou, Zhe Gan, Tamara L. Berg, Mohit Bansal, and Jingjing Liu. 2021 · 2021
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Hit: Hierarchical transformer with momentum contrast for video-text retrieval
Song Liu, Haoqi Fan, Shengsheng Qian, Yiru Chen, Wenkui Ding, and Zhongyuan Wang. 2021 · 2021
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Support-set bottlenecks for video-text representation learning
Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander G Hauptmann, Joao F. Henriques, and Andrea Vedaldi. 2021 · 2021
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A straightforward framework for video retrieval using clip
Jesús Andrés Portillo-Quintero, José Carlos Ortiz-Bayliss, and Hugo Terashima-Marín. 2021 · 2021
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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
Closest in time.