Depth Map

Depth maps, representing the distance of each pixel in an image from the camera, are crucial for numerous applications in computer vision and robotics, aiming to reconstruct accurate 3D scene geometry from 2D images or other sensor data. Current research focuses on improving the accuracy and efficiency of depth map generation, particularly through advancements in monocular depth estimation (using a single camera) and multi-view approaches (combining information from multiple cameras), often employing deep learning models like transformers and diffusion models. These improvements have significant implications for applications such as autonomous driving, augmented and virtual reality, and medical imaging, enabling more robust and realistic 3D scene understanding.