Depth Predictor

Depth prediction, the task of estimating distances from a single image or other sensor data, is a crucial area of computer vision research aiming to improve accuracy and efficiency. Current research focuses on developing sophisticated neural network architectures, including those combining convolutional neural networks and transformers, to leverage both local and global image features for more robust depth estimation. These advancements are improving the performance of monocular 3D object detection and other applications requiring accurate depth maps, leading to better 3D scene understanding and enabling more advanced robotics and autonomous systems. Furthermore, research explores adaptive sampling techniques to optimize depth sensor usage and reduce computational costs.