Object Depth

Accurately determining object depth is crucial for numerous applications, including robotics, autonomous navigation, and 3D scene understanding. Current research focuses on improving depth estimation from various sensor modalities, such as stereo vision, LiDAR, and monocular RGB images, often employing deep learning models like transformers and incorporating object-level information to enhance accuracy, particularly in challenging scenarios like adverse weather or transparent objects. These advancements are driving progress in areas such as multi-view 3D object detection and object pose estimation, leading to more robust and reliable perception systems for a wide range of applications.