VFMM3D: Releasing the Potential of Image by Vision Foundation Model for Monocular 3D Object Detection

arXiv:2404.09431v1 Announce Type: new
Abstract: Due to its cost-effectiveness and widespread availability, monocular 3D object detection, which relies solely on a single camera during inference, holds significant importance across various applications, including autonomous driving and robotics. Nevertheless, directly predicting the coordinates of objects in 3D space from monocular images poses challenges. Therefore, an effective solution involves transforming monocular images into LiDAR-like representations and employing a LiDAR-based 3D object detector to predict the 3D coordinates of objects. The key step in …

3d object 3d object detection abstract applications arxiv autonomous autonomous driving availability cost cs.cv detection driving foundation foundation model image importance inference object objects robotics type vision