Perceiving the shape and structure of the real three-dimensional world through sensors and
cameras is indispensable across various domains. The 3D reconstruction technology is …

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of
an object or scene from a set of input images. Learning-based methods have gained …

Accurate reconstruction of plant phenotypes plays a key role in optimizing sustainable
farming practices in the field of Precision Agriculture (PA). Currently, optical sensor-based …

An important objective in computer vision is to analyze multiple images and subsequently
reconstruct the shape and structure in 3D. Traditional multi-view 3D reconstruction …

Recent advancements in large generative models and real-time neural rendering using
point-based techniques pave the way for a future of widespread visual data distribution …

Deep learning (DL) in magnetic resonance imaging (MRI) shows excellent performance in
image reconstruction from undersampled k-space data. Artifact-free and high-quality MRI …

The goal of seeking advanced solutions to the descriptions of particle shape, packing and
tomographic measurement were key areas promoted by Professor Reg Davies. In this paper …

Single-view 3D reconstruction is currently approached from two dominant perspectives:
reconstruction of scenes with limited diversity using 3D data supervision or reconstruction of …

Spatial structured light (SL) can achieve three-dimensional measurements with a single
shot. As an important branch in the field of dynamic reconstruction, its accuracy, robustness …

The single-view 3D voxel reconstruction approach that relies on deep learning is inherently
constrained by its single-input nature, which fails to account for the disparities in data …