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 …

Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D
meshes generation from a single unposed image in the wild using both2D and 3D priors. In …

We study the recent progress on dynamic view synthesis (DVS) from monocular video.
Though existing approaches have demonstrated impressive results, we show a discrepancy …

Abstract We introduce Amazon Berkeley Objects (ABO), a new large-scale dataset designed
to help bridge the gap between real and virtual 3D worlds. ABO contains product catalog …

We propose an end-to-end deep learning architecture that produces a 3D shape in
triangular mesh from a single color image. Limited by the nature of deep neural network …

Recent history has seen a tremendous growth of work exploring implicit representations of
geometry and radiance, popularized through Neural Radiance Fields (NeRF). Such works …

Scene parsing aims to assign a class (semantic) label for each pixel in an image. It is a
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …

We present a learning framework for recovering the 3D shape, camera, and texture of an
object from a single image. The shape is represented as a deformable 3D mesh model of an …

Generation of 3D data by deep neural network has been attracting increasing attention in
the research community. The majority of extant works resort to regular representations such …