Datasets:
Base-to-Novel:
ImageNet-1K,
Caltech101,
Oxford Pets,
StanfordCars,
Flowers102,
Food101,
FGVC Aircraft,
SUN397,
DTD,
EuroSAT,
UCF101.
Due to various factors, the links to some datasets may be outdated or invalid.
To make it easy for you to download these datasets, we maintain a repository on HuggingFace, which contains all the datasets to be used (except ImageNet). Each dataset also includes the corresponding split_zhou_xx.json file.
Instructions for How to download these datasets:
Using the huggingface-cli command-line tool:
Install the CLI tool if not already installed.
pip install -U huggingface-hub
Download the datasets.
huggingface-cli download zhengli97/prompt_learning_dataset
Some projects from our lab may familiarize you with prompt learning:
- Open Source Paper List: https://github.com/zhengli97/Awesome-Prompt-Adapter-Learning-for-VLMs
- 中文视频解读：《视觉语言模型CLIP的提示学习方法研究》，链接
- Published Papers:
- Advancing Textual Prompt Learning with Anchored Attributes. ICCV 2025. [Paper] [Project Page] [Code] [中文解读] [中文翻译]
- PromptKD: Unsupervised Prompt Distillation for Vision-Language Models. CVPR 2024. [Paper] [Project Page] [Code] [中文解读] [中文翻译]
- Cascade Prompt Learning for Vision-Language Model Ddaptation. ECCV 2024. [Paper] [Code] [中文解读]
- Fine-Grained Visual Prompting. NeurIPS 2023. [Paper] [Code]
