Visual Transformer

Visual Transformers (ViTs) adapt the transformer architecture, known for its success in natural language processing, to image and video analysis. Current research focuses on improving ViT efficiency (e.g., through dynamic compression and lightweight architectures), enhancing feature extraction (e.g., by incorporating frequency domain information and structure-aware modules), and applying ViTs to diverse tasks including medical image analysis, 3D reconstruction, and object detection. This approach offers the potential for improved accuracy and efficiency in various computer vision applications, particularly where global context is crucial, while also addressing challenges related to computational cost and data privacy.