Supervised Fine-tuning in turn Improves Visual Foundation Models.
Xiaohu JiangYixiao GeYuying GeChun YuanYing ShanPublished in: CoRR (2024)
Keyphrases
- fine tuning
- probabilistic model
- visual tasks
- unsupervised learning
- prior knowledge
- viable alternative
- learning algorithm
- statistical model
- visual features
- classification models
- bayesian framework
- visual information
- experimental data
- machine learning algorithms
- model selection
- graphical models
- supervised learning
- low level
- decision trees