Researchers Introduce ‘SeMask’: An Effective Transformer-Framework That Incorporates Semantic Information Into The Encoder With The Help Of A Semantic Attention Operation

After demonstrating the transformer’s efficiency in the visual domain, the research community has focused on extending its use to several fields. One of these is semantic segmentation, a critical application for many areas, such as autonomous drive or medical diagnosis. The classical approach to this topic has been to use an existing pre-trained Transformer Layer as an encoder, tuning it for the segmentation task. However, this approach lacks insight into the semantic context during fine-tuning due to the relatively small …

artificial attention framework information researchers semantic transformer