[PDF] Hierarchical Surface Prediction

GAL: Geometric Adversarial Loss for Single-View 3D-Object

Keywords: 3D reconstruction · adversarial loss · geometric consistency. · point cloud · 3D neural network. 1 Introduction. Single-view 3D object 

Few-Shot Single-View 3D Object Reconstruction with Compositional

Mateusz Michalkiewicz Sarah Parisot

Learning Category-Specific Deformable 3D Models for Object

Abstract—We address the problem of fully automatic object localization and reconstruction from a single image. This is both a very.

Hierarchical Surface Prediction

chical surface prediction (HSP) for high resolution 3D object reconstruction which is organized around the observation that only a few of the voxels are in 

Online Global Non-rigid Registration for 3D Object Reconstruction

Learning 3D object models from 2D images

Learning 3D object models from 2D images HoloPose: Holistic 3D Human Reconstruction In-the-Wild A. Guler and I. Kokkinos

Domain-Adaptive Single-View 3D Reconstruction

On the other hand we impose the reconstruction to be 'realistic' by forcing it to lie on a. (learned) manifold of realistic object shapes. Our experi- ments 

Amodal 3D Reconstruction for Robotic Manipulation via Stability and

Code is available at github.com/wagnew3/ARM. Keywords: 3D Reconstruction 3D Vision

3D Shape Reconstruction From 2D Images With Disentangled

Code is available at https: //github.com/junshengzhou/3DAttriFlow. *Equal contribution. †The corresponding author is Yu-Shen Liu. This work was sup- ported 

SDF-2-SDF: Highly Accurate 3D Object Reconstruction

We make our data publicly available creating the first object reconstruction dataset to include ground-truth CAD models and RGB-D sequences from sensors of