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Adaptive multi-resolution fitting and its application to realistic head modeling
Geometric Modeling and Processing, 2004. Proceedings
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This algorithm combines the adaptive subdivision scheme with multi-resolution fitting so that the control model is subdivided locally and adaptively according to the local complexity of the point cloud ...
In this paper, we face the noise point cloud obtained from image sequences by a common camera and develop a novel algorithm of Adaptive Multi-Resolution Fitting (AMRF) for object modeling. ...
Acknowledgement: This work is supported by research funds from the NSFC (Grant No.60121302 and 60332010). The authors gratefully thank our colleagues and the anonymous reviewers for their suggestions. ...
doi:10.1109/gmap.2004.1290057
dblp:conf/gmp/XuQWTL04
fatcat:twioetglvnhy7he3rarrxyo4de
Highly Adaptive and Automated Tetrahedral Mesh Generator for Multi-Compartment Human Head Model with Deep Brain Structures in EEG
[article]
2022
arXiv
pre-print
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This paper introduces a highly adaptive and automated approach for generating Finite Element (FE) discretization for a given realistic multi-compartment human head model obtained through magnetic resonance ...
We present recursive solid angle labeling for the surface segmentation of the model and then adapt it with a set of smoothing, inflation, and optimization routines to further enhance the quality of the ...
In adaptive meshing, the GPU accelerated total ) and realistic head model (5b, 5e, 5h). ...
arXiv:2203.10000v1
fatcat:5ihsdx5sd5b6rmf44hdfvqcjnu
Experiment on Tele-immersive Communication with Tiled Display Wall over Wide Area Network
2012
Advances in Computing
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Moreover, we have tried realistic display processing of ultra resolution astronomical observation image and movie data to display in full view visualization contents with ultra resolution which is difficult ...
However, the display specification of large-scale screen system such as commercial projector and wide-area monitor to display these visual contents is low-resolution, and displaying of real video streaming ...
In order to establish high precision forecast model, it is necessary to analyze a large amount of phenomenon with ultra resolution observation image data. ...
doi:10.5923/j.ac.20120203.02
fatcat:nlgau7tlhvcs3eawdwmupohsve
Performance Analysis of Virtual Human Bodies with Clothing and Hair from Images to Animation
2018
International Journal of Advanced Research in Computer Science and Software Engineering
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We also demonstrate that a simplified 2D clothing model helps to increase the accuracy of 2D body shape estimation significantly. ...
Machine learning can be used to construct data-driven 3D human bodies, clothing, and hair. ...
For instance, the clothing model should be generic so that it adapts to different body shapes. ...
doi:10.23956/ijarcsse.v8i6.723
fatcat:rz3k6icm7fepdd5ztpnsw53faa
Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
[article]
2019
arXiv
pre-print
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Improvements in data-capture and face modeling techniques have enabled us to create high-fidelity realistic face models. ...
All these constraints make it challenging to use the high-fidelity models in tracking for commodity cameras. ...
Conclusion We proposed a deep neural network that predicts the intermediate representation and head pose of a high-fidelity 3D face model from a single image and its self-supervised domain adaptation method ...
arXiv:1907.10815v1
fatcat:5kvwovdderetto73mcjki4x67i
Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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On the other hand, the conditional generator allows for enhancing fine details and overall reality. It leverages the disentangled features to generate photo-realistic and pose-alike face images. ...
Meanwhile, a multi-scale deforming autoencoder is proposed to extract pose-related information for each frame. ...
Such an approach is able to learn highly realistic and personalized talking head models in a few-shot manner after a meta-learning. ...
doi:10.1609/aaai.v34i07.6970
fatcat:ivymkl4nm5ghjjlqimxplzxoya
VR content creation and exploration with deep learning: A survey
2020
Computational Visual Media
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It originated in the 1960s and has evolved to provide increasing immersion, interactivity, imagination, and intelligence. ...
Because deep learning systems are able to represent and compose information at various levels in a deep hierarchical fashion, they can build very powerful models which leverage large quantities of visual ...
Acknowledgements The authors would like to thank the reviewers. This work was supported by the National Natural Science Foundation of China (Grant Nos. 61902012, 61932003). ...
doi:10.1007/s41095-020-0162-z
fatcat:lgogzx26bvhn5f7uyefjkz7zny
Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose
[article]
2020
arXiv
pre-print
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On the other hand, the conditional generator allows for enhancing fine details and overall reality. It leverages the disentangled features to generate photo-realistic and pose-alike face images. ...
Meanwhile, a multi-scale deforming autoencoder is proposed to extract pose-related information for each frame. ...
Such an approach is able to learn highly realistic and personalized talking head models in a few-shot manner after a meta-learning. ...
arXiv:2003.12957v1
fatcat:ztnbksxinvd7nc4lifyhbav7nq
Controlled topology simplification
1996
IEEE Transactions on Visualization and Computer Graphics
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This is accomplished by converting an object into multi-resolution volume rasters using a controlled filtering and sampling technique. ...
We further propose an adaptive surface generation algorithm to reduce the number of triangles generated by the standard Marching Cubes. ...
We thank Arie Kaufman for his contribution to the original ideas of this project. The source of the Visible Human data set is the National Library of Medicine and the Visible Human Project. ...
doi:10.1109/2945.506228
fatcat:bid6eaon6rhfngkjfke55dy4yq
QUIC-EST: A Transmission Scheme to Maximize VoI of Multi-Stream Correlated Data Flows
[article]
2020
arXiv
pre-print
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New advanced applications, such as autonomous driving and haptic communication, require to transmit multi-sensory data and require low latency and high reliability. These applications include. ...
This mechanism allows applications to maximize the Value of Information (VoI) of the transmitted data, as we demonstrate through simulations in two realistic application scenarios. ...
However, its features can be well-adapted to interactive multi-sensory applications in which sensing data needs to be broadcast, potentially with low delay, to preserve the user's Quality of Experience ...
arXiv:2010.03831v1
fatcat:i2wal7h7gje2hlyv43co4ojboe
Video-driven Neural Physically-based Facial Asset for Production
[article]
2022
arXiv
pre-print
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In addition, our neural asset along with fast adaptation schemes can also be deployed to handle in-the-wild videos. ...
We then model the facial expression, geometry and physically-based textures using separate VAEs with a global MLP-based expression mapping across the latent spaces, to preserve characteristics across respective ...
riggable head models with high-resolution albedo and normal maps. ...
arXiv:2202.05592v3
fatcat:tfbmwzburfh7hicvdgwzd4erga
Self-Supervised Adaptation of High-Fidelity Face Models for Monocular Performance Tracking
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Abstract Improvements in data-capture and face modeling techniques have enabled us to create high-fidelity realistic face models. ...
However, driving these realistic face models requires special input data, e.g. 3D meshes and unwrapped textures. ...
Conclusion We proposed a deep neural network that predicts the intermediate representation and head pose of a high-fidelity 3D face model from a single image and its self-supervised domain adaptation method ...
doi:10.1109/cvpr.2019.00473
dblp:conf/cvpr/YoonSYP19
fatcat:gyih7ownwzbrrkegta6kvwfq34
Technical Note: Development of a 3D printed subresolution sandwich phantom for validation of brain SPECT analysis
2016
Medical Physics (Lancaster)
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Keywords 3D Printing, nuclear medicine, phantoms, quantitative imaging, brain 15 Abstract Purpose To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using ...
Methods: A fused deposition modelling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. ...
Computer analysis that fits the image dataset to a standard geometry and compares it to a 'normal database' has been used clinically and in research. ...
doi:10.1118/1.4960003
pmid:27587032
fatcat:sr662m27erfdnnitmjbbvkuxmi
Real-time expression transfer for facial reenactment
2015
ACM Transactions on Graphics
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For each frame, we jointly fit a parametric model for identity, expression, and skin reflectance to the input color and depth data, and also reconstruct the scene lighting. ...
This model, which is learned from real face scans, serves us as a statistical prior and an intermediate representation to later enable photo-realistic re-rendering of the entire face. ...
Acknowledgements We would like to thank Chen Cao and Kun Zhou for the blendshape models and comparison data, as well as Volker Blanz, Thomas Vetter, and Oleg Alexander for the provided face data. ...
doi:10.1145/2816795.2818056
fatcat:vwzo4p23vfaqvkw6p77l6cv7ua
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
[article]
2020
arXiv
pre-print
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To achieve this, we capture a large dataset of facial shape and reflectance and build on a state-of-the-art 3D texture and shape reconstruction method and successively refine its results, while generating ...
the per-pixel diffuse and specular components that are required for realistic rendering. ...
AG acknowledges funding by the EPSRC Early Career Fellowship (EP/N006259/1) and SZ from a Google Faculty Fellowship and the EPSRC Fellowship DEFORM (EP/S010203/1). ...
arXiv:2003.13845v1
fatcat:5qzhuo4qb5a4nni42fqzm6vyby
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