Zero-Shot Generative Model Adaptation via Image-Specific Prompt Learning

Author:

Guo Jiayi1,Wang Chaofei1,Wu You2,Zhang Eric3,Wang Kai3,Xu Xingqian3,Song Shiji1,Shi Humphrey3,Huang Gao1

Affiliation:

1. Tsinghua University, BNRist

2. UCAS

3. SHI Labs@Oregon & UIUC

Funder

National Key R&D Program of China

Publisher

IEEE

Reference58 articles.

1. Denoising diffusion probabilistic models;ho;NeurIPS,2020

2. Conditional Prompt Learning for Vision-Language Models

3. TransFG: A Transformer Architecture for Fine-Grained Recognition

4. Factual Probing Is [MASK]: Learning vs. Learning to Recall

5. Scaling up visual and vision-language representation learning with noisy text supervision;jia;ICML,2021

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1. ADIFT: Zero-Shot Generative Model Adaption Via Adaptive Domain-Invariant Feature Transfer;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Coping with change: Learning invariant and minimum sufficient representations for fine-grained visual categorization;Computer Vision and Image Understanding;2023-12

3. FaceCLIP: Facial Image-to-Video Translation via A Brief Text Description;IEEE Transactions on Circuits and Systems for Video Technology;2023

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