ViT Encoder

Vision Transformer (ViT) encoders are a core component of many modern computer vision models, aiming to efficiently extract meaningful representations from image data using the transformer architecture. Current research focuses on improving ViT encoder efficiency through techniques like lightweight architectures (e.g., EfficientViT), optimized training strategies (including self-supervised pre-training and knowledge distillation), and incorporating spatial and topological information for tasks such as medical image segmentation. These advancements are driving progress in various applications, including real-time object detection, medical image analysis, and scene understanding, by enabling faster and more accurate processing of visual data.