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

We propose IntraTomo, a powerful framework that combines the benefits of learning-based
and model-based approaches for solving highly ill-posed inverse problems in the Computed …

Reconstructing dynamic, time-varying scenes with computed tomography (4D-CT) is a
challenging and ill-posed problem common to industrial and medical settings. Existing 4D …

We introduce CT2Hair, a fully automatic framework for creating high-fidelity 3D hair models
that are suitable for use in downstream graphics applications. Our approach utilizes real …

The dynamics of biomolecules are crucial for our understanding of their functioning in living
systems. However, current 3D imaging techniques, such as cryogenic electron microscopy …

Visible light tomography is a promising and increasingly popular technique for fluid imaging.
However, the use of a sparse number of viewpoints in the capturing setups makes the …

Digital inline holography is an amazingly simple and effective approach for 3D imaging, to
which particle tracking velocimetry is of particular interest. Conventional digital holographic …

Flash boiling and plume interaction are common phenomena occurring in gasoline direct
injection (GDI) spray at throttling and low load engine conditions. Combined with optical …

Phase imaging techniques are an invaluable tool in microscopy for quickly examining thin
transparent specimens. Existing methods are limited to either simple and inexpensive …

Multiscale 3D characterization is widely used by materials scientists to further their
understanding of the relationships between microscopic structure and macroscopic function …