E^ 2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

C Han, Q Wang, Y Cui, Z Cao, W Wang, S Qi… - arXiv preprint arXiv …, 2023 - arxiv.org
As the size of transformer-based models continues to grow, fine-tuning these large-scale
pretrained vision models for new tasks has become increasingly parameter-intensive …
被引用次数：25 相关文章

E2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

C Han, Q Wang, Y Cui, Z Cao, W Wang… - 2023 IEEE/CVF …, 2023 - ieeexplore.ieee.org
As the size of transformer-based, models continues to grow, fine-tuning these large-scale
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E^ 2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

C Han, Q Wang, Y Cui, Z Cao, W Wang, S Qi… - arXiv e …, 2023 - ui.adsabs.harvard.edu
As the size of transformer-based models continues to grow, fine-tuning these large-scale
pretrained vision models for new tasks has become increasingly parameter-intensive …

E^ 2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

C Han, Q Wang, Y Cui, Z Cao… - Proceedings of the …, 2023 - openaccess.thecvf.com
As the size of transformer-based models continues to grow, fine-tuning these large-scale pre-
trained vision models for new tasks has become increasingly parameter-intensive …

E2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

C Han, Q Wang, Y Cui, Z Cao, W Wang… - 2023 IEEE/CVF …, 2023 - computer.org
As the size of transformer-based, models continues to grow, fine-tuning these large-scale
pretrained vision models for new tasks has become increasingly parameter-intensive …