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Vision-language models (VLMs) classify the query video by calculating a similarity score between the visual features and text-based class label representations.
Hmdb: a large video database for human motion recognition
Hildegard Kuehne, Hueihan Jhuang, Estíbaliz Garrote, Tomaso Poggio, and Thomas Serre · 2011
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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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
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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
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The” something something” video database for learning and evaluating visual common sense
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fruend, Peter Yianilos, Moritz Mueller-Freitag, et al · 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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Zero-shot action recognition with error-correcting output codes
Jie Qin, Li Liu, Ling Shao, Fumin Shen, Bingbing Ni, Jiaxin Chen, and Yunhong Wang · 2017
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Alternative semantic representations for zero-shot human action recognition
Qian Wang and Ke Chen · 2017
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Rethinking zero-shot video classification: End-to-end training for realistic applications
Biagio Brattoli, Joseph Tighe, Fedor Zhdanov, Pietro Perona, and Krzysztof Chalupka · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
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Elaborative rehearsal for zero-shot action recognition
Shizhe Chen and Dong Huang · 2021
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Clip2video: Mastering video-text retrieval via image clip
Han Fang, Pengfei Xiong, Luhui Xu, and Yu Chen · 2021
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Open-vocabulary object detection via vision and language knowledge distillation
Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, and Yin Cui · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 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
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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, et al · 2021
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Actionclip: A new paradigm for video action recognition
Mengmeng Wang, Jiazheng Xing, and Yong Liu · 2021
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Videoclip: Contrastive pre-training for zero-shot video-text understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, and Christoph Feichtenhofer · 2021
What does a platypus look like? generating customized prompts for zero-shot image classification
Sarah Pratt, Ian Covert, Rosanne Liu, and Ali Farhadi · 2022
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Denseclip: Language-guided dense prediction with context-aware prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie Zhou, and Jiwen Lu · 2022
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Centerclip: Token clustering for efficient text-video retrieval
Shuai Zhao, Linchao Zhu, Xiaohan Wang, and Yi Yang · 2022
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Test of time: Instilling video-language models with a sense of time
Piyush Bagad, Makarand Tapaswi, and Cees GM Snoek · 2023
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Vindlu: A recipe for effective video-and-language pretraining
Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, and Gedas Bertasius · 2023
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Florence: A new foundation model for computer vision
Lu Yuan, Dongdong Chen, Yi-Ling Chen, Noel Codella, Xiyang Dai, Jianfeng Gao, Houdong Hu, Xuedong Huang, Boxin Li, Chunyuan Li, et al · 2021
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Tip-adapter: Training-free clip-adapter for better vision-language modeling
Renrui Zhang, Rongyao Fang, Wei Zhang, Peng Gao, Kunchang Li, Jifeng Dai, Yu Qiao, and Hongsheng Li · 2021
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Decoupling zero-shot semantic segmentation
Jian Ding, Nan Xue, Gui-Song Xia, and Dengxin Dai · 2022
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Visual prompt tuning
Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge Belongie, Bharath Hariharan, and Ser-Nam Lim · 2022
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Prompting visual-language models for efficient video understanding
Chen Ju, Tengda Han, Kunhao Zheng, Ya Zhang, and Weidi Xie · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
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Clip4clip: An empirical study of clip for end to end video clip retrieval and captioning
Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, and Tianrui Li · 2022
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al · 2023
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Video-chatgpt: Towards detailed video understanding via large vision and language models
Muhammad Maaz, Hanoona Rasheed, Salman Khan, and Fahad Shahbaz Khan · 2023
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Chils: Zero-shot image classification with hierarchical label sets
Zachary Novack, Julian McAuley, Zachary Chase Lipton, and Saurabh Garg · 2023
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Fine-tuned clip models are efficient video learners
Hanoona Rasheed, Muhammad Uzair Khattak, Muhammad Maaz, Salman Khan, and Fahad Shahbaz Khan · 2023
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Waffling around for performance: Visual classification with random words and broad concepts
Karsten Roth, Jae Myung Kim, A Koepke, Oriol Vinyals, Cordelia Schmid, and Zeynep Akata · 2023
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Vita-clip: Video and text adaptive clip via multimodal prompting
Syed Talal Wasim, Muzammal Naseer, Salman Khan, Fahad Shahbaz Khan, and Mubarak Shah · 2023
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Aim: Adapting image models for efficient video action recognition
Taojiannan Yang, Yi Zhu, Yusheng Xie, Aston Zhang, Chen Chen, and Mu Li · 2023
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Towards universal representation for unseen action recognition
Yi Zhu, Yang Long, Yu Guan, Shawn Newsam, and Ling Shao · 2023
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