Medical image segmentation plays a pivotal role in ensuring accurate diagnosis. Traditional methods are predominantly monomodal, relying solely on image data. These image-only methods require large ...

Text in the real world is extremely diverse, yet current text dataset does not reflect such diversity very well. To bridge this gap, we proposed TextSeg, a large-scale fine-annotated and multi-purpose ...

This repository contains the source code of our proposed multimodal image segmentation frameworks. The network architectures and training procedure are provided to reproduce the experimental results ...

With the rapid development of natural language processing technology, text segmentation has become an important task in text processing. However, existing text segmentation methods often perform ...