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Recent video and language pretraining frameworks lack the ability to generate sentences.
A simple weight decay can improve generalization
Anders Krogh and John A Hertz · 1992
Earlier work this paper cites.
Natural language description of human activities from video images based on concept hierarchy of actions
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BLEU: a method for automatic evaluation of machine translation
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Earlier work this paper cites.
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Earlier work this paper cites.
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Michael Gutmann and Aapo Hyvärinen · 2010
Earlier work this paper cites.
A thousand frames in just a few words: Lingual description of videos through latent topics and sparse object stitching
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Earlier work this paper cites.
Translating video content to natural language descriptions
Marcus Rohrbach, Wei Qiu, Ivan Titov, Stefan Thater, Manfred Pinkal, and Bernt Schiele · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
CIDEr: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
Earlier work this paper cites.
Msr-vtt: A large video description dataset for bridging video and language
Jun Xu, Tao Mei, Ting Yao, and Yong Rui · 2016
Earlier work this paper cites.
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Joao Carreira and Andrew Zisserman · 2017
Earlier work this paper cites.
The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 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
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Video question answering via gradually refined attention over appearance and motion
Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, and Yueting Zhuang · 2017
Earlier work this paper cites.
Jointly localizing and describing events for dense video captioning
Yehao Li, Ting Yao, Yingwei Pan, Hongyang Chao, and Tao Mei · 2018
Earlier work this paper cites.
Bidirectional attentive fusion with context gating for dense video captioning
Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu, and Yong Xu · 2018
Earlier work this paper cites.
Watch, listen, and describe: Globally and locally aligned cross-modal attentions for video captioning
Xin Wang, Yuan-Fang Wang, and William Yang Wang · 2018
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Rethinking spatiotemporal feature learning for video understanding
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
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Luowei Zhou, Chenliang Xu, and Jason Corso · 2018
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Motion guided spatial attention for video captioning
Shaoxiang Chen and Yu-Gang Jiang · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
A semantics-assisted video captioning model trained with scheduled sampling
Haoran Chen, Ke Lin, Alexander Maye, Jianmin Li, and Xiaolin Hu · 2020
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Multi-modal transformer for video retrieval
Valentin Gabeur, Chen Sun, Karteek Alahari, and Cordelia Schmid · 2020
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Multimodal pretraining for dense video captioning
Gabriel Huang, Bo Pang, Zhenhai Zhu, Clara Rivera, and Radu Soricut · 2020
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A better use of audio-visual cues: Dense video captioning with bi-modal transformer
Vladimir Iashin and Esa Rahtu · 2020
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Multi-modal dense video captioning
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Open-ended long-form video question answering via hierarchical convolutional self-attention networks
Zhang · 2019
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A case study on combining asr and visual features for generating instructional video captions
Jack Hessel, Bo Pang, Zhenhai Zhu, and Radu Soricut · 2019
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Joint syntax representation learning and visual cue translation for video captioning
Jingyi Hou, Xinxiao Wu, Wentian Zhao, Jiebo Luo, and Yunde Jia · 2019
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ViLBERT: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
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HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips
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Bruno Korbar, Fabio Petroni, Rohit Girdhar, and Lorenzo Torresani · 2020
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Jie Lei, Liwei Wang, Yelong Shen, Dong Yu, Tamara Berg, and Mohit Bansal · 2020
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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
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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
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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
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Object relational graph with teacher-recommended learning for video captioning
Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, Peijin Wang, Weiming Hu, and Zheng-Jun Zha · 2020
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ActBERT: Learning global-local video-text representations
Linchao Zhu and Yi Yang · 2020
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Multichannel attention refinement for video question answering
Yueting Zhuang, Dejing Xu, Xin Yan, Wenzhuo Cheng, Zhou Zhao, Shiliang Pu, and Jun Xiao · 2020
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Noise estimation using density estimation for self-supervised multimodal learning
Elad Amrani, Rami Ben-Ari, Daniel Rotman, and Alex Bronstein · 2021
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ViViT: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid · 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
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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
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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 · 2021
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Look before you speak: Visually contextualized utterances
Paul Hongsuck Seo, Arsha Nagrani, and Cordelia Schmid · 2021
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DECEMBERT: Learning from noisy instructional videos via dense captions and entropy minimization
Zineng Tang, Jie Lei, and Mohit Bansal · 2021
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Just Ask: Learning to answer questions from millions of narrated videos
Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, and Cordelia Schmid · 2021
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