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The core of video understanding tasks, such as recognition, captioning, and tracking, is to automatically detect objects or actions in a video and analyze their temporal evolution.
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Karen Simonyan and Andrew Zisserman · 2014
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Activitynet: A large-scale video benchmark for human activity understanding
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Fast r-cnn
Ross Girshick · 2015
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Visual tracking with fully convolutional networks
Lijun Wang, Wanli Ouyang, Xiaogang Wang, and Huchuan Lu · 2015
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Modeling spatial-temporal clues in a hybrid deep learning framework for video classification
Zuxuan Wu, Xi Wang, Yu-Gang Jiang, Hao Ye, and Xiangyang Xue · 2015
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Fully-convolutional siamese networks for object tracking
Luca Bertinetto, Jack Valmadre, Joao F Henriques, Andrea Vedaldi, and Philip HS Torr · 2016
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Convolutional two-stream network fusion for video action recognition
Christoph Feichtenhofer, Axel Pinz, and Andrew Zisserman · 2016
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Msr-vtt: A large video description dataset for bridging video and language
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Joao Carreira and Andrew Zisserman · 2017
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Beam search strategies for neural machine translation
Markus Freitag and Yaser Al-Onaizan · 2017
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Video captioning with attention-based lstm and semantic consistency
Lianli Gao, Zhao Guo, Hanwang Zhang, Xing Xu, and Heng Tao Shen · 2017
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The” something something” video database for learning and evaluating visual common sense
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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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
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Dense-captioning events in videos
Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, and Juan Carlos Niebles · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Zero-shot action recognition with error-correcting output codes
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Attention is all you need
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Qian Wang and Ke Chen · 2017
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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
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A short note about kinetics-600
Joao Carreira, Eric Noland, Andras Banki-Horvath, Chloe Hillier, and Andrew Zisserman · 2018
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Less is more: Picking informative frames for video captioning
Yangyu Chen, Shuhui Wang, Weigang Zhang, and Qingming Huang · 2018
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Autoregressive times series methods for time domain astronomy
Eric D Feigelson, G Jogesh Babu, and Gabriel A Caceres · 2018
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Tvqa: Localized, compositional video question answering
Jie Lei, Licheng Yu, Mohit Bansal, and Tamara L Berg · 2018
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Jointly localizing and describing events for dense video captioning
Yehao Li, Ting Yao, Yingwei Pan, Hongyang Chao, and Tao Mei · 2018
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Sibnet: Sibling convolutional encoder for video captioning
Sheng Liu, Zhou Ren, and Junsong Yuan · 2018
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Trackingnet: A large-scale dataset and benchmark for object tracking in the wild
Matthias Muller, Adel Bibi, Silvio Giancola, Salman Alsubaihi, and Bernard Ghanem · 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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A closer look at spatiotemporal convolutions for action recognition
Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, and Manohar Paluri · 2018
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Bidirectional attentive fusion with context gating for dense video captioning
Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu, and Yong Xu · 2018
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Towards universal representation for unseen action recognition
Yi Zhu, Yang Long, Yu Guan, Shawn Newsam, and Ling Shao · 2018
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Spatio-temporal dynamics and semantic attribute enriched visual encoding for video captioning
Nayyer Aafaq, Naveed Akhtar, Wei Liu, Syed Zulqarnain Gilani, and Ajmal Mian · 2019
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Learning discriminative model prediction for tracking
Goutam Bhat, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2019
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Motion guided spatial attention for video captioning
Shaoxiang Chen and Yu-Gang Jiang · 2019
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Deep learning for video captioning: A review
Shaoxiang Chen, Ting Yao, and Yu-Gang Jiang · 2019
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Atom: Accurate tracking by overlap maximization
Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, and Michael Felsberg · 2019
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Lasot: A high-quality benchmark for large-scale single object tracking
Heng Fan, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Hexin Bai, Yong Xu, Chunyuan Liao, and Haibin Ling · 2019
Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid · 2021
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Is space-time attention all you need for video understanding?
Gedas Bertasius, Heng Wang, and Lorenzo Torresani · 2021
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Space-time mixing attention for video transformer
Adrian Bulat, Juan Manuel Perez Rua, Swathikiran Sudhakaran, Brais Martinez, and Georgios Tzimiropoulos · 2021
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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
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Multiscale vision transformers
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Gta: Global temporal attention for video action understanding
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Slowfast networks for video recognition
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 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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Got-10k: A large high-diversity benchmark for generic object tracking in the wild
Lianghua Huang, Xin Zhao, and Kaiqi Huang · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
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Siamrpn++: Evolution of siamese visual tracking with very deep networks
Bo Li, Wei Wu, Qiang Wang, Fangyi Zhang, Junliang Xing, and Junjie Yan · 2019
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Streamlined dense video captioning
Jonghwan Mun, Linjie Yang, Zhou Ren, Ning Xu, and Bohyung Han · 2019
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Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, and Abhinav Shrivastava · 2021
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Movinets: Mobile video networks for efficient video recognition
Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, and Boqing Gong · 2021
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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
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Learning target candidate association to keep track of what not to track
Christoph Mayer, Martin Danelljan, Danda Pani Paudel, and Luc Van Gool · 2021
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Video transformer network
Daniel Neimark, Omri Bar, Maya Zohar, and Dotan Asselmann · 2021
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Keeping your eye on the ball: Trajectory attention in video transformers
Mandela Patrick, Dylan Campbell, Yuki Asano, Ishan Misra, Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, and Joao F Henriques · 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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Learning spatio-temporal transformer for visual tracking
Bin Yan, Houwen Peng, Jianlong Fu, Dong Wang, and Huchuan Lu · 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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Mixformer: End-to-end tracking with iterative mixed attention
Yutao Cui, Cheng Jiang, Limin Wang, and Gangshan Wu · 2022
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Aiatrack: Attention in attention for transformer visual tracking
Shenyuan Gao, Chunluan Zhou, Chao Ma, Xinggang Wang, and Junsong Yuan · 2022
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Asm-loc: Action-aware segment modeling for weakly-supervised temporal action localization
Bo He, Xitong Yang, Le Kang, Zhiyu Cheng, Xin Zhou, and Abhinav Shrivastava · 2022
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Swinbert: End-to-end transformers with sparse attention for video captioning
Kevin Lin, Linjie Li, Chung-Ching Lin, Faisal Ahmed, Zhe Gan, Zicheng Liu, Yumao Lu, and Lijuan Wang · 2022
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Rethinking resolution in the context of efficient video recognition
Chuofan Ma, Qiushan Guo, Yi Jiang, Ping Luo, Zehuan Yuan, and Xiaojuan Qi · 2022
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Towards grand unification of object tracking
Bin Yan, Yi Jiang, Peize Sun, Dong Wang, Zehuan Yuan, Ping Luo, and Huchuan Lu · 2022
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Joint feature learning and relation modeling for tracking: A one-stream framework
Botao Ye, Hong Chang, Bingpeng Ma, Shiguang Shan, and Xilin Chen · 2022
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Merlot reserve: Neural script knowledge through vision and language and sound
Rowan Zellers, Jiasen Lu, Ximing Lu, Youngjae Yu, Yanpeng Zhao, Mohammadreza Salehi, Aditya Kusupati, Jack Hessel, Ali Farhadi, and Yejin Choi · 2022
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Unifying event detection and captioning as sequence generation via pre-training
Qi Zhang, Yuqing Song, and Qin Jin · 2022
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Seqtrack: Sequence to sequence learning for visual object tracking
Xin Chen, Houwen Peng, Dong Wang, Huchuan Lu, and Han Hu · 2023
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Align and attend: Multimodal summarization with dual contrastive losses
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Univtg: Towards unified video-language temporal grounding
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Resformer: Scaling vits with multi-resolution training
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Autoregressive visual tracking
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Vidiff: Translating videos via multi-modal instructions with diffusion models
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Vid2seq: Large-scale pretraining of a visual language model for dense video captioning
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Ma-lmm: Memory-augmented large multimodal model for long-term video understanding
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Building an open-vocabulary video clip model with better architectures, optimization and data
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