Work

Prompting Visual-Language Models for Efficient Video Understanding

Year: 2022

Type: conference-paper

Source: Lecture notes in computer science

Parent work: Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXV

DOI: 10.1007/978-3-031-19833-5_7

Authors: Chen Ju, Tengda Han, Kunhao Zheng, Ya Zhang, Weidi Xie

Institutions: Shanghai Jiao Tong University, University of Oxford

Language: English

Topic: Multimodal Machine Learning Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: DeepMind, Science and Technology Commission of Shanghai Municipality, Engineering and Physical Sciences Research Council, National Key Research and Development Program of China

Awards: Visual AI: An Open World Interpretable Visual Transformer, G5047994227, G7814127966

OpenAlex ID: W4312480274

FWCI: 30.35

Cites: 91

Cited by: 458

Related to: 10