Object Detection Using Yolov8 and Depth Estimation Using Monocular Vision

Object detection and depth estimation are two important tasks in computer vision that have many applications in autonomous driving, robotics, and augmented reality. In this paper, we propose a framework that combines the state-of-the-art object detector YOLOv8 with a monocular depth estimation network to achieve accurate and efficient 3D scene understanding. Our framework consists of two stages: First, we use YOLOv8 to detect and localize the objects in the 2D image; second, we use a monocular depth estimation network to estimate the depth map of the scene.