Object Localization

Object localization, the task of precisely determining the location and extent of objects within an image or scene, is a core problem in computer vision with applications ranging from robotics to medical imaging. Current research emphasizes improving robustness and accuracy under challenging conditions like distribution shifts (e.g., varying weather or viewpoints) and limited data, often employing convolutional neural networks (CNNs), transformers, and graph-based methods for feature extraction and object representation. These advancements are crucial for enhancing the reliability and performance of numerous applications, including autonomous navigation, object manipulation by robots, and medical image analysis.