Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …

The proliferation of technologies, such as extended reality (XR), has increased the demand
for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications …

Implicit neural representations (INRs) have emerged as a powerful paradigm in scene
reconstruction and computer graphics, showcasing remarkable results. By utilizing neural …

X-ray known for its ability to reveal internal structures of objects is expected to provide richer
information for 3D reconstruction than visible light. Yet existing NeRF algorithms overlook …

In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive,
hierarchical neural rendering pipeline for tomography. Through a combination of neural …

X-ray is widely applied for transmission imaging due to its stronger penetration than natural
light. When rendering novel view X-ray projections, existing methods mainly based on NeRF …

Abstract Limited-Angle Computed Tomography (LACT) is a non-destructive 3D imaging
technique used in a variety of applications ranging from security to medicine. The limited …

This paper proposes a novel and fast self-supervised solution for sparse-view CBCT
reconstruction (Cone Beam Computed Tomography) that requires no external training data …

Medical image arbitrary-scale super-resolution (MIASSR) has recently gained widespread
attention, aiming to supersample medical volumes at arbitrary scales via a single model …

Emerging neural reconstruction techniques based on tomography (eg, NeRF, NeAT, and
NeRP) have started showing unique capabilities in medical imaging. In this work, we …