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We consider the attributes of a point cloud as samples of a vector-valued volumetric function at discrete positions.
Calculation of average psnr differences between rd-curves
G. Bjøntegaard · 2001
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Adaptive run-length/golomb-rice encoding of quantized generalized gaussian sources with unknown statistics
H.S. Malvar · 2006
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S. Pateux and J. Jung · 2007
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MeshLab: an Open-Source Mesh Processing Tool
P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, and G. Ranzuglia · 2008
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Point cloud attribute compression with graph transform
C. Zhang, D. Florêncio, and C. Loop · 2014
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S. Han, H. Mao, and W. J. Dally · 2015
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End-to-end optimization of nonlinear transform codes for perceptual quality
J. Ballé, V. Laparra, and E. P. Simoncelli · 2016
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Attribute compression for sparse point clouds using graph transforms
R. A. Cohen, D. Tian, and A. Vetro · 2016
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Compression of 3d point clouds using a region-adaptive hierarchical transform
R. L. de Queiroz and P. A. Chou · 2016
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Graph-based compression of dynamic 3d point cloud sequences
D. Thanou, P. A. Chou, and P. Frossard · 2016
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Variable rate image compression with recurrent neural networks
G. Toderici, S. M. O’Malley, S. J. Hwang, D. Vincent, D. Minnen, S. Baluja, M. Covell, and R. Sukthankar · 2016
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End-to-end optimized image compression
J. Ballé, V. Laparra, and E. P. Simoncelli · 2017
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Motion-compensated compression of dynamic voxelized point clouds
R. L. de Queiroz and P. A. Chou · 2017
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Motion-compensated compression of dynamic voxelized point clouds
R. L. de Queiroz and P. A. Chou · 2017
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Design, implementation, and evaluation of a point cloud codec for tele-immersive video
R. Mekuria, K. Blom, and P. Cesar · 2017
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Full resolution image compression with recurrent neural networks
G. Toderici, D. Vincent, N. Johnston, S. J. Hwang, D. Minnen, J. Shor, and M. Covell · 2017
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Efficient nonlinear transforms for lossy image compression
J. Ballé · 2018
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Variational image compression with a scale hyperprior
J. Ballé, D. Minnen, S. Singh, S. J. Hwang, and N. Johnston · 2018
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Scalable methods for 8-bit training of neural networks
R. Banner, I. Hubara, E. Hoffer, and D. Soudry · 2018
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8i voxelized surface light field (8iVSLF) dataset
M. Krivokuća, P. A. Chou, and P. Savill · 2018
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Joint autoregressive and hierarchical priors for learned image compression
D. Minnen, J. Ballé, and G. Toderici · 2018
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Dynamic polygon clouds: representation and compression for VR/AR
E. Pavez, P. A. Chou, R. L. de Queiroz, and A. Ortega · 2018
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Compression of plenoptic point clouds using the region-adaptive hierarchical transform
G. Sandri, R. de Queiroz, and P. A. Chou · 2018
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Training deep neural networks with 8-bit floating point numbers
N. Wang, J. Choi, D. Brand, C.-Y. Chen, and K. Gopalakrishnan · 2018
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Deep neural network compression with single and multiple level quantization
Y. Xu, Y. Wang, A. Zhou, W. Lin, and H. Xiong · 2018
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A framework for surface light field compression
X. Zhang, P. A. Chou, M. Sun, M. Tang, S. Wang, S. Ma, and W. Gao · 2018
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Deep learning-based point cloud coding: A behavior and performance study
A. F. R. Guarda, N. M. M. Rodrigues, and F. Pereira · 2019
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Point cloud coding: Adopting a deep learning-based approach
A. F. R. Guarda, N. M. M. Rodrigues, and F. Pereira · 2019
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The relightables: Volumetric performance capture of humans with realistic relighting
K. Guo, P. Lincoln, P. Davidson, J. Busch, X. Yu, M. Whalen, G. Harvey, S. Orts-Escolano, R. Pandey, J. Dourgarian, D. Tang, A. Tkach, A. Kowdle, E. Cooper, M. Dou, S. Fanello, G. Fyffe, C. Rhemann, J. Taylor, P. Debevec, and S. Izadi · 2019
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Video-based point-cloud-compression standard in mpeg: From evidence collection to committee draft [standards in a nutshell]
E. S. Jang, M. Preda, K. Mammou, A. M. Tourapis, J. Kim, D. B. Graziosi, S. Rhyu, and M. Budagavi · 2019
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On an improvement of raht to exploit attribute correlation
S. Lasserre and D. Flynn · 2019
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Occupancy networks: Learning 3d reconstruction in function space
L. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger · 2019
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Scalable model compression by entropy penalized reparameterization
D. Oktay, J. Ballé, S. Singh, and A. Shrivastava · 2019
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Rate-utility optimized streaming of volumetric media for augmented reality
J. Park, P. A. Chou, and J. Hwang · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove · 2019
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Learning convolutional transforms for lossy point cloud geometry compression
M. Quach, G. Valenzise, and F. Dufaux · 2019
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Compression of plenoptic point clouds
G. Sandri, R. L. de Queiroz, and P. A. Chou · 2019
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Point cloud compression incorporating region of interest coding
G. Sandri, V. F. Figueiredo, P. A. Chou, and R. de Queiroz · 2019
Nerv: Neural reflectance and visibility fields for relighting and view synthesis, 2020
P. P. Srinivasan, B. Deng, X. Zhang, M. Tancik, B. Mildenhall, and J. T. Barron · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
P. Sun, H. Kretzschmar, X. Dotiwalla, A. Chouard, V. Patnaik, P. Tsui, J. Guo, Y. Zhou, Y. Chai, B. Caine, V. Vasudevan, W. Han, J. Ngiam, H. Zhao, A. Timofeev, S. Ettinger, M. Krivokon, A. Gao, A. Joshi, Y. Zhang, J. Shlens, Z. Chen, and D. Anguelov · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains, 2020
M. Tancik, P. P. Srinivasan, B. Mildenhall, S. Fridovich-Keil, N. Raghavan, U. Singhal, R. Ramamoorthi, J. T. Barron, and R. Ng · 2020
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Deep implicit volume compression
D. Tang, S. Singh, P. A. Chou, C. Häne, M. Dou, S. Fanello, J. Taylor, P. Davidson, O. G. Guleryuz, Y. Zhang, S. Izadi, A. Tagliasacchi, S. Bouaziz, and C. Keskin · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields, 2021
J. T. Barron, B. Mildenhall, M. Tancik, P. Hedman, R. Martin-Brualla, and P. P. Srinivasan · 2021
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Integer alternative for the region-adaptive hierarchical transform
G. P. Sandri, P. A. Chou, M. Krivokuća, and R. L. de Queiroz · 2019
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Emerging MPEG standards for point cloud compression
S. Schwarz, M. Preda, V. Baroncini, M. Budagavi, P. Cesar, P. A. Chou, R. A. Cohen, M. Krivokuća, S. Lasserre, Z. Li, J. Llach, K. Mammou, R. Mekuria, O. Nakagami, E. Siahaan, A. Tabatabai, A. Tourapis, and V. Zakharchenko · 2019
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And the bit goes down: Revisiting the quantization of neural networks
P. Stock, A. Joulin, R. Gribonval, B. Graham, and H. Jégou · 2019
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Hybrid 8-bit floating point (hfp8) training and inference for deep neural networks
X. Sun, J. Choi, C.-Y. Chen, N. Wang, S. Venkataramani, V. Viji Srinivasan, X. Cui, W. Zhang, and K. Gopalakrishnan · 2019
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Haq: Hardware-aware automated quantization with mixed precision
K. Wang, Z. Liu, Y. Lin, J. Lin, and S. Han · 2019
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Deep autoencoder-based lossy geometry compression for point clouds
W. Yan, Y. Shao, S. Liu, T. H. Li, Z. Li, and G. Li · 2019
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