Perspective Transformer Nets: Learning Single-View 3D Object PDF

2019. 11. 1. The goal of image-based 3D reconstruction is to infer the 3D geometry and structure of objects and scenes from one or multiple 2D images.

Voxel-Based 3D Object Reconstruction from Single 2D Image Using

2021. 9. 17. More precisely we can divide the conversion of 2D images to 3D model reconstruction into three generations. The first generation learns the 3D ...

Learning Pose-invariant 3D Object Reconstruction from Single-view

Learning 3D shape. Single view supervision. Domain confusion. Adversarial learning. ABSTRACT. Learning to reconstruct 3D shapes using 2D images is an active

3D object reconstruction and 6D-pose estimation from 2D shape for

2022. 3. 2. In the proposed pipeline recognition and labeling of objects in 2D images deliver 2D segment silhouettes that are com- pared with the 2D ...

3D-RCNN: Instance-Level 3D Object Reconstruction via Render

In this work we argue for the importance of a rich 3D scene model which can reason about object instances. A 2D image is a complex function of multiple attribu

Perspective Transformer Nets: Learning Single-View 3D Object

for 3D object reconstruction when the projection loss is involved. generative model for 3D volumetric data and combined it with a 2D image embedding ...

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

Single-view 3D object reconstruction is a fundamental task in computer vision the conditional discriminator network combines a 2D CNN to extract image.

A Point Set Generation Network for 3D Object Reconstruction From

That is why the majority of extant works on using deep nets for 3D data resort to either volumetric grids or collections of images (2D views of the geometry).

Photometric Mesh Optimization for Video-Aligned 3D Object

1. Introduction. The choice of 3D representation plays a crucial role in 3D reconstruction problems from 2D images. Classical multi-.

3D Shape Reconstruction From 2D Images With Disentangled

[19] further extend such framework to capture the semantic part of object in 2D images. Pan et al. [28] im- prove the ability to generate complex shape by

[PDF] Perspective Transformer Nets: Learning Single-View 3D Object

Image-based 3D Object Reconstruction: State-of-the-Art and Trends