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Learning to Reconstruct Texture-less Deformable Surfaces from a Single View
[article]
2018
arXiv
pre-print
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Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. ...
By contrast, recovering the 3D shape of texture-less surfaces remains an open problem, and essentially relates to Shape-from-Shading. ...
Acknowledgments This work was supported in part by a Swiss National Foundation for Research grant. ...
arXiv:1803.08908v2
fatcat:2mszsqtnobbyfkjmodvnksrxha
Learning to Reconstruct Texture-Less Deformable Surfaces from a Single View
2018
2018 International Conference on 3D Vision (3DV)
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Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. ...
Our experiments show that meshes are ill-suited to handle texture-less 3D reconstruction in our context. ...
Acknowledgments This work was supported in part by a Swiss National Foundation for Research grant. ...
doi:10.1109/3dv.2018.00075
dblp:conf/3dim/BednarikFS18
fatcat:xdmccjdnofh37jy34s6nunyrcu
Deep Textured 3D Reconstruction of Human Bodies
[article]
2018
arXiv
pre-print
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In this paper, we propose a deep learning based solution for textured 3D reconstruction of human body shapes from a single view RGB image. ...
Further, a calibration-free environment adds additional complexity to both - reconstruction and texture recovery. ...
In order to ensure that reconstruction is feasible from single as well as multiple views, we choose random number of views from available views for training a mesh in each iteration. ...
arXiv:1809.06547v1
fatcat:cysa6kojvrd6zeqvxcmwf3ntva
Textured Mesh Generation Using Multi-View and Multi-Source Supervision and Generative Adversarial Networks
2021
Remote Sensing
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This study focuses on reconstructing accurate meshes with high-resolution textures from single images. ...
The mesh-reconstruction network estimates a deformation map, which is used to deform a template mesh to the shape of the target object in the input image, and a low-resolution texture. ...
Conclusions In this study, we proposed a method for reconstructing a high-resolution textured mesh from a single image. ...
doi:10.3390/rs13214254
fatcat:m7nwlbqp55gqbmcodx7ap4rhhe
Self-supervised Single-view 3D Reconstruction via Semantic Consistency
[article]
2020
arXiv
pre-print
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We learn a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture and camera pose of a target object with a collection of 2D images and silhouettes. ...
To the best of our knowledge, we are the first to try and solve the single-view reconstruction problem without a category-specific template mesh or semantic keypoints. ...
Inspired by this intuition, we learn a single-view reconstruction model from a collection of images and silhouettes. ...
arXiv:2003.06473v1
fatcat:kf4djdg7d5ddzb2wibdlzxfltu
Topologically-Aware Deformation Fields for Single-View 3D Reconstruction
[article]
2022
arXiv
pre-print
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At inference time, given a single image, we reconstruct the underlying 3D shape by first implicitly deforming each 3D point in the object space to the learned category-specific canonical space using the ...
The 3D shapes are generated implicitly as deformations to a category-specific signed distance field and are learned in an unsupervised manner solely from unaligned image collections and their poses without ...
The proposed approach, TARS, tackles the problem of single-view reconstruction by implicitly learning to deform different object instances to a learned category specific mean shape. ...
arXiv:2205.06267v2
fatcat:4tnngz3oirh7boxubsmv42c43i
Learning Category-Specific Mesh Reconstruction from Image Collections
[chapter]
2018
Lecture Notes in Computer Science
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We present a learning framework for recovering the 3D shape, camera, and texture of an object from a single image. ...
Texture Camera Shape f Fig. 1 : Given an annotated image collection of an object category, we learn a predictor f that can map a novel image I to its 3D shape, camera pose, and texture. ...
Single-view 3D Reconstruction. We show sample reconstruction results on images from the CUB test set in Figure 5 . ...
doi:10.1007/978-3-030-01267-0_23
fatcat:p3yaq7ctdbh4zfrpwjtlo23caq
Online Adaptation for Consistent Mesh Reconstruction in the Wild
[article]
2020
arXiv
pre-print
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We first learn a category-specific 3D reconstruction model from a collection of single-view images of the same category that jointly predicts the shape, texture, and camera pose of an image. ...
This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. ...
We learn a category-specific 3D mesh reconstruction model that jointly predicts the shape, texture, and camera pose from single-view images, which is capable of capturing asymmetric non-rigid motion deformation ...
arXiv:2012.03196v1
fatcat:vpvkmtu3qvav7gpgs4ty5ryugq
PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction
[article]
2020
arXiv
pre-print
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In our simple non-parametric solution, the generated Peeled Depth maps are back-projected to 3D space to obtain a complete textured 3D shape. ...
Given a monocular RGB image, we learn these Peeled maps in an end-to-end generative adversarial fashion using our novel framework - PeelGAN. ...
Conclusion We present a novel representation to reconstruct a textured human model from a single RGB image using Peeled Depth and RGB maps. ...
arXiv:2002.06664v2
fatcat:itfkq7qf6vc3jhoa4qmgnatnr4
Learning Category-Specific Mesh Reconstruction from Image Collections
[article]
2018
arXiv
pre-print
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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 object category where a shape is parameterized by a learned mean shape and per-instance predicted deformation. ...
Single-view 3D Reconstruction. We show sample reconstruction results on images from the CUB test set in Figure 5 . ...
arXiv:1803.07549v2
fatcat:ivunso4vqfav5pi65ftqjmsh2e
When 3D Reconstruction Meets Ubiquitous RGB-D Images
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
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3D reconstruction from a single image is a classical problem in computer vision. However, it still poses great challenges for the reconstruction of daily-use objects with irregular 1 shapes. ...
The learning of 3D reconstruction is defined as a category modeling problem, in which a model for each category is trained to encode category-specific knowledge for 3D reconstruction. ...
[9] proposed to learn 3D primitives from RGB-D images for single-view reconstruction of indoor environment. ...
doi:10.1109/cvpr.2014.95
dblp:conf/cvpr/ZhangSSZS14
fatcat:7a4ofyaqufeehbubjmgw33ezjm
Local deformation models for monocular 3D shape recovery
2008
2008 IEEE Conference on Computer Vision and Pattern Recognition
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While using a texture-based approach, we show that our models are effective to reconstruct from single videos poorly-textured surfaces of arbitrary shape, made of materials as different as cardboard, that ...
By contrast with typical statistical learning methods that build models for specific object shapes, we learn local deformation models, and combine them to reconstruct surfaces of arbitrary global shapes ...
Introduction Without a deformation model, recovering the 3D shape of a non-rigid surface from a single view is an ill-posed problem. ...
doi:10.1109/cvpr.2008.4587499
dblp:conf/cvpr/SalzmannUF08
fatcat:rzjgyy2ug5di3jwkggvuddek74
Monocular 3D Reconstruction of Locally Textured Surfaces
2012
IEEE Transactions on Pattern Analysis and Machine Intelligence
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At the heart of our algorithm are a learned mapping from intensity patterns to the shape of local surface patches and a principled approach to piecing together the resulting local shape estimates. ...
Here, we propose a novel approach to monocular deformable shape recovery that can operate under complex lighting and handle partially textured surfaces. ...
INTRODUCTION Many algorithms have been proposed to recover the 3D shape of a deformable surface from either single views or short video sequences. ...
doi:10.1109/tpami.2011.196
pmid:22516648
fatcat:gywsvcv2trej5k6ezdsb5x4ugm
Detailed Avatar Recovery from Single Image
[article]
2021
arXiv
pre-print
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This paper presents a novel framework to recover detailed avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, texture, and viewpoints. ...
We use the deep neural networks to refine the 3D shape in a Hierarchical Mesh Deformation (HMD) framework, utilizing the constraints from body joints, silhouettes, and per-pixel shading information. ...
TEXTURE COMPLETION Synthesizing complete texture for the reconstructed human model from a single image is also a challenging problem, since only less than half of the texture is visible and can be retrieved ...
arXiv:2108.02931v1
fatcat:66rbl5dhnvdsvbatfoo5znaabm
PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
[article]
2019
arXiv
pre-print
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Using PIFu, we propose an end-to-end deep learning method for digitizing highly detailed clothed humans that can infer both 3D surface and texture from a single image, and optionally, multiple input images ...
Furthermore, while previous techniques are designed to process either a single image or multiple views, PIFu extends naturally to arbitrary number of views. ...
The multi-view PIFu is fine-tuned from the models trained for single-view surface reconstruction and texture inference with a learning rate of 1 × 10 −4 and 2 epochs. ...
arXiv:1905.05172v3
fatcat:aq7mo4wt6nea5cpka24azjswba
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