Pro-tuning: Unified Prompt Tuning for Vision Tasks

Author:

Nie Xing1ORCID,Ni Bolin1,Chang Jianlong2ORCID,Meng Gaofeng1ORCID,Huo Chunlei3ORCID,Xiang Shiming1ORCID,Tian Qi2ORCID

Affiliation:

1. Department of State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Science, Beijing, China

2. Huawei Cloud & AI, Beijing, China

3. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

innoHK project

the National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

2. Few-Shot Incremental Object Detection in Aerial Imagery via Dual-Frequency Prompt;IEEE Transactions on Geoscience and Remote Sensing;2024

3. UPetu: A Unified Parameter-Efficient Fine-Tuning Framework for Remote Sensing Foundation Model;IEEE Transactions on Geoscience and Remote Sensing;2024

4. AiRs: Adapter in Remote Sensing for Parameter-Efficient Transfer Learning;IEEE Transactions on Geoscience and Remote Sensing;2024

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