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Keeping you up to date with the latest trends and best performing architectures in this fast evolving field in computer science. Selecting papers by comparative results, citations and influence we educate you on the latest research. Consider supporting us on Patreon.com/PapersRead for feedback and ideas.
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Wednesday Dec 21, 2022
Revisiting Classifier: Transferring Vision-Language Models for Video Recognition
Wednesday Dec 21, 2022
Wednesday Dec 21, 2022
Transferring knowledge from task-agnostic pre-trained deep models for downstream tasks is an important topic in computer vision research. Along with the growth of computational capacity, we now have open-source vision-language pre-trained models in large scales of the model architecture and amount of data. In this study, we focus on transferring knowledge for video classification tasks. Conventional methods randomly initialize the linear classifier head for vision classification, but they leave the usage of the text encoder for downstream visual recognition tasks undiscovered. In this paper, we revise the role of the linear classifier and replace the classifier with different knowledge from the pre-trained model. 2022: Wenhao Wu, Zhun Sun, Wanli Ouyang Ranked #1 on Action Recognition on ActivityNet https://arxiv.org/pdf/2207.01297v3.pdf
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