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Survey on Deep Learning-Based Point Cloud Compression
2022
Frontiers in Signal Processing
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Point clouds are becoming essential in key applications with advances in capture technologies leading to large volumes of data. Compression is thus essential for storage and transmission. ...
Finally, the link between existing point cloud compression research and research problems to relevant areas of adjacent fields, such as rendering in computer graphics, mesh compression and point cloud ...
statement must describe the contributions of individual authors referred to by their initials and, in doing so, all authors agree to be accountable for the content of the work. ...
doi:10.3389/frsip.2022.846972
doaj:efaf611e79344f78ab943340b1e56141
fatcat:umnadvlgz5ep5bfnxr2w3uvrqe
An overview of ongoing point cloud compression standardization activities: video-based (V-PCC) and geometry-based (G-PCC)
2020
APSIPA Transactions on Signal and Information Processing
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This article presents an overview of the recent standardization activities for point cloud compression (PCC). ...
A point cloud is a 3D data representation used in diverse applications associated with immersive media including virtual/augmented reality, immersive telepresence, autonomous driving and cultural heritage ...
cloud video over a band-limited network. ...
doi:10.1017/atsip.2020.12
fatcat:heoofmb2xzg4lpmi3npc67cjfm
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2311.17245v4 fatcat:rfqrlsyoxjd2ppluiec65y65yuOther Versions
In summary, LightGaussian achieves an averaged compression rate over 15x while boosting the FPS from 139 to 215, enabling an efficient representation of complex scenes on Mip-NeRF 360, Tank and Temple ...
Recent advancements in real-time neural rendering using point-based techniques have paved the way for the widespread adoption of 3D representations. ...
For the Gaussian location, we draw from point cloud compression and adopt octree-based lossless compression into our framework. ...
arXiv:2311.17245v5
fatcat:aa2w5wkpkva5vkztihk5cx7l5q
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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., +, TIP 2020 4772-4787 Data compression 3D Point Cloud Attribute Compression Using Geometry-Guided Sparse Representation. ...
Liu, F., +, TIP 2020 1628-1640
Geometry
3D Point Cloud Attribute Compression Using Geometry-Guided Sparse
Representation. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference Metric
[article]
2022
arXiv
pre-print
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estimate the subjective quality of point clouds. ...
In the dataset, each reference point cloud is augmented with 31 types of impairments (e.g., Gaussian noise, contrast distortion, local missing, and compression loss) at 7 distortion levels. ...
[38] build the connection between the quality and compression parameters (e.g., quantification step) of point clouds, which can be used to guide point cloud compression strategy with certain rate constraints ...
arXiv:2012.11895v4
fatcat:lclmw6bmczag5p7e3kjwremfbq
MPED: Quantifying Point Cloud Distortion based on Multiscale Potential Energy Discrepancy
[article]
2022
arXiv
pre-print
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For sparse point clouds, a distortion quantification methods is work as a loss function to guide the training of deep neural networks for unsupervised learning tasks (e.g., point cloud reconstruction, ...
Specifically, for dense point clouds, a distortion quantification method is used to predict human subjective scores and optimize the selection of human perception tasks parameters, such as compression ...
This work was supported by the National Key R&D Project of China (2018YFE0206700) and National Natural Science Foundation of China (61971282, U20A20185). ...
arXiv:2103.02850v4
fatcat:4cmxdvux5bechj2fqbpd2fkubu
Density-preserving Deep Point Cloud Compression
[article]
2022
arXiv
pre-print
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Local density of point clouds is crucial for representing local details, but has been overlooked by existing point cloud compression methods. ...
To mitigate the clustered points issue in existing methods, we design a novel sub-point convolution layer, and an upsampling block with adaptive scale. ...
In this paper we are focusing on the more lossy compression in favor of higher compression ratio.
Point Cloud Compression. Traditional point cloud compression algorithms Point Cloud Upsampling. ...
arXiv:2204.12684v1
fatcat:e4ao2ln3fbhlbn45pb77smipbi
Point Cloud Quality Assessment: Dataset Construction and Learning-based No-Reference Metric
2022
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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estimate the subjective quality of point clouds. ...
In the dataset, each reference point cloud is augmented with 31 types of impairments (e.g., Gaussian noise, contrast distortion, local missing, and compression loss) at 7 distortion levels. ...
[38] build the connection between the quality and compression parameters (e.g., quantification step) of point clouds, which can be used to guide point cloud compression strategy with certain rate constraints ...
doi:10.1145/3550274
fatcat:7jrp5xvaajdfbmlgv3qyfcso4m
2021 Index IEEE Transactions on Image Processing Vol. 30
2021
IEEE Transactions on Image Processing
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
., +, TIP 2021 4840-4854 Where to Prune: Using LSTM to Guide Data-Dependent Soft Pruning. Point Relation-Aware Network for 3D Point Cloud Analysis. ...
., +, TIP 2021 418-430 Optical radar Hierarchical Attention Learning of Scene Flow in 3D Point Clouds. ...
doi:10.1109/tip.2022.3142569
fatcat:z26yhwuecbgrnb2czhwjlf73qu
Table of contents
2020
IEEE Transactions on Image Processing
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Pak-Kong Lun 859 3D Point Cloud Attribute Compression Using Geometry-Guided Sparse Representation .................................. .................................................................... ...
Qin 2845 Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering .......................... .................................................................... S. ...
doi:10.1109/tip.2019.2940373
fatcat:i7hktzn4wrfz5dhq7hj75u6esa
A framework for realistic 3D tele-immersion
2013
Proceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications - MIRAGE '13
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Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite different from the experience of meeting face to face. ...
Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic experiences to a multitude of users that for them will feel much more similar to having ...
In particular, we use octree compression for point clouds [15] (available in PCL) and MPEG-4 SC3DMC coding [18] for triangle meshes. ...
doi:10.1145/2466715.2466718
dblp:conf/mirage/FechtelerHEBSWSMKMCMODAZ13
fatcat:mpfmtj5w3rg37mjsmlbot3kgk4
Neural Fields in Visual Computing and Beyond
[article]
2022
arXiv
pre-print
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These methods, which we call neural fields, have seen successful application in the synthesis of 3D shapes and image, animation of human bodies, 3D reconstruction, and pose estimation. ...
Recent advances in machine learning have created increasing interest in solving visual computing problems using a class of coordinate-based neural networks that parametrize physical properties of scenes ...
Medial Fields [RLS * 21] represent the local thickness of the geometry which can be derived from the medial axis. ...
arXiv:2111.11426v4
fatcat:yteqzbu6gvgdzobnfzuqohix2e
Adaptive modeling and distribution of large natural scenes
2009
ACM SIGMultimedia Records
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We optimize the viewpoint culling requests on server-side by providing an adapted datastructure and we prepare the ground for our further work on scalability and deployment of distributed 3D streaming ...
The topological structure and the geometry of the plants are represented by generalized cylinders. ...
Conclusion and Perspectives In this chapter, we have shown how we can transmit interdependent pieces of data resulting from progressive compression of 3D models over best effort lossy networks. ...
doi:10.1145/1738921.1738927
fatcat:spn2sjexqncf7bwz5hcrpxtpzq
D3.8 - Software Components final version
2020
Zenodo
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testing towards facilitating integration and use in the pilots, as well as software description, technical evaluations and including technical documentation report targeting its use beyond the scope of ...
Acknowledgement of previously published material and of the work of others has been made through appropriate citation, quotation or both. ...
Optimization of
memory use
TRL7:
Optimization for
parallelized
multiple
encoding
Features Low delay
encoding and
decoding
Lossy geometry
coding using
octree
occupancy
Lossy attribute ...
doi:10.5281/zenodo.4439676
fatcat:yvgn446pzndyhaxmuqxzhyfke4
Overview of Volume Rendering
[chapter]
2005
Visualization Handbook
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An octree is the 3D extension of a quadtree [218] , which is the 2D extension of a binary tree. ...
All are lossy to a certain degree, depending on a set tolerance. An alternative compression strategy is the use of more efficient sampling grids, such as the BCC grids. ...
doi:10.1016/b978-012387582-2/50009-5
fatcat:gthzcwcaanhuvhpmab7ii6r5fa
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