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Temporal language grounding in videos aims to localize the temporal span relevant to the given query sentence.
Exploiting temporal relationships in video moment localization with natural language
Songyang Zhang, Jinsong Su, and Jiebo Luo. 2019b · 1908
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Excl: Extractive clip localization using natural language descriptions
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Long short-term memory
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Recurrent neural networks
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Machine reading comprehension: The role of contextualized language models and beyond
Zhuosheng Zhang, Hai Zhao, and Rui Wang. 2020c · 2005
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Grounding action descriptions in videos
Michaela Regneri, Marcus Rohrbach, Dominikus Wetzel, Stefan Thater, Bernt Schiele, and Manfred Pinkal. 2013 · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014 · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
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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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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Hollywood in homes: Crowdsourcing data collection for activity understanding
Gunnar A Sigurdsson, Gül Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta. 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
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman. 2017 · 2017
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Tall: Temporal activity localization via language query
Jiyang Gao, Chen Sun, Zhenheng Yang, and Ram Nevatia. 2017 · 2017
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Dense-captioning events in videos
Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, and Juan Carlos Niebles. 2017 · 2017
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Race: Large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Temporally grounding natural sentence in video
Jingyuan Chen, Xinpeng Chen, Lin Ma, Zequn Jie, and Tat-Seng Chua. 2018 · 2018
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Tvqa: Localized, compositional video question answering
Ccnet: Criss-cross attention for semantic segmentation
Zilong Huang, Xinggang Wang, Lichao Huang, Chang Huang, Yunchao Wei, and Wenyu Liu. 2019 · 2019
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Debug: A dense bottom-up grounding approach for natural language video localization
Chujie Lu, Long Chen, Chilie Tan, Xiaolin Li, and Jun Xiao. 2019 · 2019
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Dream: A challenge data set and models for dialogue-based reading comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, and Claire Cardie. 2019 · 2019
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Language-driven temporal activity localization: A semantic matching reinforcement learning model
Weining Wang, Yan Huang, and Liang Wang. 2019 · 2019
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Multilevel language and vision integration for text-to-clip retrieval
Huijuan Xu, Kun He, Bryan A Plummer, Leonid Sigal, Stan Sclaroff, and Kate Saenko. 2019 · 2019
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Jie Lei, Licheng Yu, Mohit Bansal, and Tamara Berg. 2018 · 2018
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Attentive moment retrieval in videos
Meng Liu, Xiang Wang, Liqiang Nie, Xiangnan He, Baoquan Chen, and Tat-Seng Chua. 2018 · 2018
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Find and focus: Retrieve and localize video events with natural language queries
Dian Shao, Yu Xiong, Yue Zhao, Qingqiu Huang, Yu Qiao, and Dahua Lin. 2018 · 2018
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Multi-modal circulant fusion for video-to-language and backward
Aming Wu and Yahong Han. 2018 · 2018
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Semantic proposal for activity localization in videos via sentence query
Shaoxiang Chen and Yu-Gang Jiang. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Dual encoding for zero-example video retrieval
Jianfeng Dong, Xirong Li, Chaoxi Xu, Shouling Ji, Yuan He, Gang Yang, and Xun Wang. 2019 · 2019
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To find where you talk: Temporal sentence localization in video with attention based location regression
Yitian Yuan, Tao Mei, and Wenwu Zhu. 2019 · 2019
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Accurate temporal action proposal generation with relation-aware pyramid network
Jialin Gao, Zhixiang Shi, Guanshuo Wang, Jiani Li, Yufeng Yuan, Shiming Ge, and Xi Zhou. 2020 · 2020
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Location-aware graph convolutional networks for video question answering
Deng Huang, Peihao Chen, Runhao Zeng, Qing Du, Mingkui Tan, and Chuang Gan. 2020 · 2020
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Moment retrieval via cross-modal interaction networks with query reconstruction
Zhijie Lin, Zhou Zhao, Zhu Zhang, Zijian Zhang, and Deng Cai. 2020 · 2020
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Temporally grounding language queries in videos by contextual boundary-aware prediction
Jingwen Wang, Lin Ma, and Wenhao Jiang. 2020 · 2020
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G-tad: Sub-graph localization for temporal action detection
Mengmeng Xu, Chen Zhao, David S. Rojas, Ali Thabet, and Bernard Ghanem. 2020 · 2020
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Dense regression network for video grounding
Runhao Zeng, Haoming Xu, Wenbing Huang, Peihao Chen, Mingkui Tan, and Chuang Gan. 2020 · 2020
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Vision-language navigation with self-supervised auxiliary reasoning tasks
Fengda Zhu, Yi Zhu, Xiaojun Chang, and Xiaodan Liang. 2020 · 2020
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