Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning-Reference-Cited by-同舟云学术

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Visual Query Tuning: Towards Effective Usage of Intermediate Representations for Parameter and Memory Efficient Transfer Learning

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Tu Cheng-Hao¹,Mai Zheda¹,Chao Wei-Lun¹

Affiliation:

1. The Ohio State University

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205336.pdf?arnumber=10205336

Reference59 articles.

1. An image is worth 16×16 words: Transformers for image recognition at scale;dosovitskiy;International Conference on Learning Representations,2021

2. Panda: Prompt transfer meets knowledge distillation for efficient model adaptation;zhong;ArXiv Preprint,2022

3. Analyzing Redundancy in Pretrained Transformer Models

4. Point Transformer

5. Head2toe: Utilizing intermediate rep-resentations for better transfer learning;evci;International Conference on Machine Learning,2022

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1. Frequency-Aware Multi-Modal Fine-Tuning for Few-Shot Open-Set Remote Sensing Scene Classification;IEEE Transactions on Multimedia;2024

2. Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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