Depth Image

Depth images, representing 3D scene information as 2D arrays of depth values, are central to numerous applications, primarily aiming for accurate and efficient 3D scene understanding. Current research focuses on improving depth image quality through denoising and completion techniques, often employing convolutional neural networks (CNNs) and generative adversarial networks (GANs), as well as developing novel algorithms for depth-based tasks like object detection, pose estimation, and scene reconstruction. These advancements significantly impact robotics, augmented reality, medical imaging, and other fields requiring robust 3D perception, enabling improved automation, navigation, and analysis capabilities.