3D reconstruction from single images - Ping, Guiju (Nanyang Technological University, 2024)
3D reconstruction from single images is a fundamental task in computer vision, and it has a wide range of applications, including anime films, robot object interaction, AR, VR and 3D games. Due to the task's complexity and significant information loss from 3D to 2D, traditional methods are ineffective. The use of deep learning and large-scale datasets to learn priori knowledge is a promising direction and has achieved varying degrees of success. However, 3D deep learning requires a large number of annotated 3D objects. These annotations are usually tedious and time-consuming. In view of this fact, this thesis presents a method to generate annotated 3D datasets automatically, and experiments demonstrate the effectiveness of the generated datasets for 3D deep learning tasks.