Multi Task Vision Transformer

Multi-task vision transformers (MVTs) aim to improve efficiency and performance in computer vision by training a single model to perform multiple tasks simultaneously, unlike traditional single-task approaches. Current research focuses on developing novel MVT architectures, such as those employing mixture-of-experts for efficient resource allocation and parameter-efficient transfer learning methods to adapt large pre-trained models to various downstream tasks. These advancements are proving valuable in diverse applications, including medical image analysis (e.g., diagnosing intracerebral hemorrhage or screening for myopia), driver behavior monitoring, and scene understanding, demonstrating the potential of MVTs to enhance the speed and accuracy of various computer vision systems.