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3D Object Reconstruction

20 papers with code · Computer Vision

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Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

NeurIPS 2016 tensorflow/models

We demonstrate the ability of the model in generating 3D volume from a single 2D image with three sets of experiments: (1) learning from single-class objects; (2) learning from multi-class objects and (3) testing on novel object classes.

3D OBJECT RECONSTRUCTION

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

2 Apr 2016chrischoy/3D-R2N2

Inspired by the recent success of methods that employ shape priors to achieve robust 3D reconstructions, we propose a novel recurrent neural network architecture that we call the 3D Recurrent Reconstruction Neural Network (3D-R2N2).

3D OBJECT RECONSTRUCTION 3D RECONSTRUCTION

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

ECCV 2018 nywang16/Pixel2Mesh

We propose an end-to-end deep learning architecture that produces a 3D shape in triangular mesh from a single color image.

3D OBJECT RECONSTRUCTION

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction

21 Jun 2017chenhsuanlin/3D-point-cloud-generation

Conventional methods of 3D object generative modeling learn volumetric predictions using deep networks with 3D convolutional operations, which are direct analogies to classical 2D ones.

3D OBJECT RECONSTRUCTION POINT CLOUD GENERATION

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

CVPR 2017 charlesq34/pointnet-autoencoder

Our final solution is a conditional shape sampler, capable of predicting multiple plausible 3D point clouds from an input image.

#3 best model for 3D Reconstruction on Data3D−R2N2 (using extra training data)

3D OBJECT RECONSTRUCTION 3D OBJECT RECONSTRUCTION FROM A SINGLE IMAGE 3D RECONSTRUCTION

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

ICCV 2019 hzxie/Pix2Vox

Then, a context-aware fusion module is introduced to adaptively select high-quality reconstructions for each part (e. g., table legs) from different coarse 3D volumes to obtain a fused 3D volume.

3D OBJECT RECONSTRUCTION 3D RECONSTRUCTION

3D Object Reconstruction from a Single Depth View with Adversarial Learning

26 Aug 2017Yang7879/3D-RecGAN

In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial networks.

3D OBJECT RECONSTRUCTION