Object Box

Object boxes, representing the location and extent of objects within images or videos, are central to many computer vision tasks, with current research focusing on improving their accuracy, efficiency, and interpretability. This involves developing novel algorithms and model architectures, such as those based on diffusion models, transformers, and graph neural networks, often incorporating techniques like active learning and box embedding to optimize training and enhance performance. Improvements in object box detection have significant implications for applications ranging from medical image analysis and autonomous driving to large language model evaluation and accessibility technologies for visually impaired individuals.