GitHub

PromptKD: Unsupervised Prompt Distillation for Vision-Language Models

🔥 Some other prompt learning projects from our lab may interest you: Advancing Textual Prompt Learning with Anchored Attributes. Zheng Li, Yibing Song, Ming-Ming Cheng, Xiang Li#, Jian Yang#. In this ...
IEEE

IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-Training

Abstract: In medical Vision-Language Pre-training (VLP), significant work focuses on extracting text and image features from clinical reports and medical images. Yet, existing methods may overlooked ...
GitHub

SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance

In semi-supervised semantic segmentation, a model is trained with a limited number of labeled images along with a large corpus of unlabeled images to reduce the high annotation effort. While previous ...
IEEE

Multi-Task Paired Masking With Alignment Modeling for Medical Vision-Language Pre-Training

Abstract: In recent years, the growing demand for medical imaging diagnosis has placed a significant burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) methods have ...
Microsoft

BEiT: BERT Pre-Training of Image Transformers

We introduce a self-supervised vision representation model BEiT, which stands for Bidirectional Encoder representation from Image Transformers. Following BERT developed in the natural language ...