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3D VAE-Attention Network: A Parallel System for Single-view 3D Reconstruction
2018
Pacific Conference on Computer Graphics and Applications
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To tackle this problem, we propose a parallel system named 3D VAE-attention network (3VAN) for single view 3D reconstruction. ...
3D object reconstruction from single view image is a challenge task. ...
Our main contribution is to build an end-to-end parallel system 3D VAE-attention network (3VAN) for single view 3D reconstruction task. Our proposed 3VAN consists of two branches. ...
doi:10.2312/pg.20181279
dblp:conf/pg/HuYZYZ18
fatcat:wfpufsvxw5cxlgihxbftzg6fsq
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
[article]
2016
arXiv
pre-print
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Our key contributions are methods for training voxel-based variational autoencoders, a user interface for exploring the latent space learned by the autoencoder, and a deep convolutional neural network ...
We address challenges unique to voxel-based representations, and empirically evaluate our models on the ModelNet benchmark, where we demonstrate a 51.5% relative improvement in the state of the art for ...
Acknowledgments This research was made possible by grants and support from Renishaw plc and the Edinburgh Centre For Robotics. ...
arXiv:1608.04236v2
fatcat:jurty7fbhbgwfazvjnsin46xk4
Generative And Discriminative Voxel Modeling With Convolutional Neural Networks
2016
Zenodo
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Our key contributions are methods for training voxel-based variational autoencoders, a user interface for exploring the latent space learned by the autoencoder, and a deep convolutional neural network ...
We address challenges unique to voxel-based representations, and empirically evaluate our models on the ModelNet benchmark, where we demonstrate a 51.5% relative improvement in the state of the art for ...
Acknowledgments This research was made possible by grants and support from Renishaw plc and the Edinburgh Centre For Robotics. ...
doi:10.5281/zenodo.802260
fatcat:4oe7w3qci5aobd42wa44p3s7ua
A Point Set Generation Network for 3D Object Reconstruction from a Single Image
[article]
2016
arXiv
pre-print
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In experiments not only can our system outperform state-of-the-art methods on single image based 3d reconstruction benchmarks; but it also shows a strong performance for 3d shape completion and promising ...
Generation of 3D data by deep neural network has been attracting increasing attention in the research community. ...
Second, we allow multiple reconstruction candidates for a single input image. This design reflects the fact that a single image cannot fully determine the reconstruction of a 3D shape. ...
arXiv:1612.00603v2
fatcat:5cqdthedjrblnfwbmdqhf23wym
A Point Set Generation Network for 3D Object Reconstruction from a Single Image
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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In experiments not only can our system outperform state-ofthe-art methods on single image based 3d reconstruction benchmarks; but it also shows strong performance for 3d shape completion and promising ...
Generation of 3D data by deep neural network has been attracting increasing attention in the research community. ...
Second, we allow multiple reconstruction candidates for a single input image. This design reflects the fact that a single image cannot fully determine the reconstruction of a 3D shape. ...
doi:10.1109/cvpr.2017.264
dblp:conf/cvpr/FanSG17
fatcat:2wkzarvwnjb4xo7aspguqeghei
DRI-MVSNet: A depth residual inference network for multi-view stereo images
2022
PLoS ONE
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Three-dimensional (3D) image reconstruction is an important field of computer vision for restoring the 3D geometry of a given scene. ...
This study proposes a cascaded depth residual inference network, called DRI-MVSNet, that uses a cross-view similarity-based feature map fusion module for residual inference. ...
reconstruction is the process of rebuilding the 3D geometry of a scene from a single view or multiple views. ...
doi:10.1371/journal.pone.0264721
pmid:35320265
pmcid:PMC8942269
fatcat:nyrzqymhwvcqtmzxatwsbqtn7q
A Survey on Generative Adversarial Networks: Variants, Applications, and Training
[article]
2020
arXiv
pre-print
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The Generative Models have gained considerable attention in the field of unsupervised learning via a new and practical framework called Generative Adversarial Networks (GAN) due to its outstanding data ...
Therefore, stable training is a crucial issue in different applications for the success of GAN. ...
(3D) volumetric convolution networks have led to the application of GAN to generate 3D objects. 3D-GAN [81] expands the system from 2D-GAN to 3D-GAN. ...
arXiv:2006.05132v1
fatcat:gyjezuh5sfdilkp43ydsea5cwa
Estimating Egocentric 3D Human Pose in Global Space
[article]
2021
arXiv
pre-print
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To tackle these limitations, we present a new method for egocentric global 3D body pose estimation using a single head-mounted fisheye camera. ...
Egocentric 3D human pose estimation using a single fisheye camera has become popular recently as it allows capturing a wide range of daily activities in unconstrained environments, which is difficult for ...
[5] estimate the 3d body pose from two headmounted pinhole cameras with a recurrent neural network. To avoid inconvenience of large setup, some researchers use a single wide-view fisheye camera. ...
arXiv:2104.13454v3
fatcat:6kaczumgd5hwpnfseh3jyi4b5a
A Survey on Deep Geometry Learning: From a Representation Perspective
[article]
2020
arXiv
pre-print
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In recent years, 3D computer vision and Geometry Deep Learning gain more and more attention. Many advanced techniques for 3D shapes have been proposed for different applications. ...
Therefore, in this survey, we review recent development in deep learning for 3D geometry from a representation perspective, summarizing the advantages and disadvantages of different representations in ...
[116] also proposed Deep Implicit Surface Networks (DISNs) for single-view 3D reconstruction based on SDFs. ...
arXiv:2002.07995v2
fatcat:pustwlu5freypnccfrculkqvei
A survey on deep geometry learning: From a representation perspective
2020
Computational Visual Media
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In recent years, 3D computer vision and geometry deep learning have gained ever more attention. Many advanced techniques for 3D shapes have been proposed for different applications. ...
Unlike 2D images, which can be uniformly represented by a regular grid of pixels, 3D shapes have various representations, such as depth images, multi-view images, voxels, point clouds, meshes, implicit ...
[9] also proposed deep implicit surface networks (DISNs) for single-view 3D reconstruction based on SDFs. ...
doi:10.1007/s41095-020-0174-8
fatcat:kpoynaixq5esbek63bovybisfa
Pore Space Reconstruction of Shale Using Improved Variational Autoencoders
2021
Geofluids
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Therefore, this paper proposes an improved VAE to reconstruct shale based on VAE and Fisher information, using a real 3D shale image as a TI, and saves the parameters of neural networks to describe the ...
The recent branch of deep learning, variational auto-encoders (VAEs), has good capabilities of extracting characteristics for reconstructing similar images with the training image (TI). ...
information for 3D reconstruction. ...
doi:10.1155/2021/5545411
fatcat:upejierbrvh2vn6uosv2226xl4
Compositional Scene Representation Learning via Reconstruction: A Survey
[article]
2022
arXiv
pre-print
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Moreover, learning compositional scene representations via reconstruction can greatly reduce the need for training data annotations. ...
In this survey, we first discuss representative methods that either learn from a single viewpoint or multiple viewpoints without object-level supervision, then the applications of compositional scene representations ...
Compared with learning from a single view- point, learning from multiple viewpoints requires extra mod- eling of viewpoints. ...
arXiv:2202.07135v1
fatcat:dxowzvbhhrbujnhezpdln26adm
Deep Neural Mobile Networking
[article]
2020
arXiv
pre-print
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This makes monitoring and managing the multitude of network elements intractable with existing tools and impractical for traditional machine learning algorithms that rely on hand-crafted feature engineering ...
This thesis attacks important problems in the mobile networking area from various perspectives by harnessing recent advances in deep neural networks. ...
In Training Parallelism is also essential for mobile system, as mobile data usually come asynchronously from different sources. ...
arXiv:2011.05267v1
fatcat:yz2zp5hplzfy7h5kptmho7mbhe
A survey on generative adversarial networks for imbalance problems in computer vision tasks
2021
Journal of Big Data
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In recent years, Generative Adversarial Neural Networks (GANs) have gained immense attention by researchers across a variety of application domains due to their capability to model complex real-world image ...
After that, we propose a taxonomy to summarize GANs based techniques for addressing imbalance problems in computer vision tasks into three major categories: 1. ...
Also, we acknowledge the members of the Autonomous and Intelligent Systems Unit, Tekniker, for valuable discussions and collaborations. ...
doi:10.1186/s40537-021-00414-0
pmid:33552840
pmcid:PMC7845583
fatcat:g3p6hbjuj5c5vbe23ms4g6ed6q
Recovering 3D Human Mesh from Monocular Images: A Survey
[article]
2022
arXiv
pre-print
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2022 pre-print arXiv:2203.01923v1 fatcat:lxg7tokzyjfkrirf6dkatzih2m
Meanwhile, continuous efforts are devoted to improving the quality of 3D mesh labels for a wide range of datasets. ...
Since the release of statistical body models, 3D human mesh recovery has been drawing broader attention. ...
The ground-truth 3D poses are captured in a multi-view markerless motion capture system. ...
arXiv:2203.01923v2
fatcat:vb6xa5wdsrhdxd2ebvg54qq2m4
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