This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

The reconstruction of 3D object from a single image is an important task in the field of
computer vision. In recent years, 3D reconstruction of single image using deep learning …

Learning-based 3D reconstruction methods have shown impressive results. However, most
methods require 3D supervision which is often hard to obtain for real-world datasets …

As 3D point clouds become the representation of choice for multiple vision and graphics
applications, the ability to synthesize or reconstruct high-resolution, high-fidelity point clouds …

Estimating the complete 3D point cloud from an incomplete one is a key problem in many
vision and robotics applications. Mainstream methods (eg, PCN and TopNet) use Multi-layer …

This paper presents a new approach for 3D shape generation, enabling direct generative
modeling on a continuous implicit representation in wavelet domain. Specifically, we …

3D reconstruction is a longstanding ill-posed problem, which has been explored for decades
by the computer vision, computer graphics, and machine learning communities. Since 2015 …

In this paper, we propose a novel generative adversarial network (GAN) for 3D point clouds
generation, which is called tree-GAN. To achieve state-of-the-art performance for multi-class …

We propose SDFDiff, a novel approach for image-based shape optimization using
differentiable rendering of 3D shapes represented by signed distance functions (SDFs) …

Computed tomography (CT) can provide a 3D view of the patient's internal organs,
facilitating disease diagnosis, but it incurs more radiation dose to a patient and a CT scanner …