3D Box

3D bounding boxes are crucial for representing objects within 3D scenes, particularly in applications like autonomous driving and scene understanding. Current research focuses on improving the accuracy and efficiency of 3D box detection and adaptation, addressing challenges such as noisy data and the need for extensive manual annotation. This involves developing novel algorithms, including uncertainty-aware frameworks and semi-supervised learning approaches, to refine box estimations from various data sources like LiDAR and images. Advances in this area are vital for improving the performance of numerous computer vision and robotics systems.