Instance Level Recognition

Instance-level recognition aims to identify and segment individual objects within an image, going beyond simple object detection to provide precise boundaries and classifications. Current research focuses on developing universal image embeddings, capable of recognizing objects across diverse domains, often employing transformer-based architectures and techniques like online distillation to improve efficiency and accuracy. This field is crucial for advancing applications such as smart home interaction, document analysis, and large-scale image retrieval, where precise object identification is essential. The development of robust and efficient universal models is a key challenge driving ongoing research.