Fetching the paper…
Reading the bibliography…
Conventional video compression approaches use the predictive coding architecture and encode the corresponding motion information and residual information.
The jpeg still picture compression standard
G. K. Wallace · 1992
Earlier work this paper cites.
The jpeg 2000 still image compression standard
A. Skodras, C. Christopoulos, and T. Ebrahimi · 2001
Earlier work this paper cites.
Multi-scale structural similarity for image quality assessment
Z. Wang, E. Simoncelli, A. Bovik, et al · 2003
Earlier work this paper cites.
Overview of the h. 264/avc video coding standard
T. Wiegand, G. J. Sullivan, G. Bjontegaard, and A. Luthra · 2003
Earlier work this paper cites.
Overview of the high efficiency video coding(hevc) standard
G. J. Sullivan, J.-R. Ohm, W.-J. Han, T. Wiegand, et al · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Hausser, C. Hazirbas, V. Golkov, P. Van Der Smagt, D. Cremers, and T. Brox · 2015
Earlier work this paper cites.
S. Han, H. Mao, and W. J. Dally · 2015
Earlier work this paper cites.
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 · 2015
Earlier work this paper cites.
End-to-end optimized image compression
J. Ballé, V. Laparra, and E. P. Simoncelli · 2016
Earlier work this paper cites.
Cu partition mode decision for hevc hardwired intra encoder using convolution neural network
Z. Liu, X. Yu, Y. Gao, S. Chen, X. Ji, and D. Wang · 2016
Earlier work this paper cites.
Forecast and methodology, 2016-2021, white paper
C. V. networking Index · 2016
Earlier work this paper cites.
Soft-to-hard vector quantization for end-to-end learning compressible representations
E. Agustsson, F. Mentzer, M. Tschannen, L. Cavigelli, R. Timofte, L. Benini, and L. V. Gool · 2017
Earlier work this paper cites.
Learning to inpaint for image compression
M. H. Baig, V. Koltun, and L. Torresani · 2017
Earlier work this paper cites.
Deepcoder: A deep neural network based video compression
T. Chen, H. Liu, Q. Shen, T. Yue, X. Cao, and Z. Ma · 2017
Cited alongside, same era.
Spatially adaptive image compression using a tiled deep network
D. Minnen, G. Toderici, M. Covell, T. Chinen, N. Johnston, J. Shor, S. J. Hwang, D. Vincent, and S. Singh · 2017
Cited alongside, same era.
Optical flow estimation using a spatial pyramid network
A. Ranjan and M. J. Black · 2017
Cited alongside, same era.
Real-time adaptive image compression
O. Rippel and L. Bourdev · 2017
Cited alongside, same era.
Neural network-based arithmetic coding of intra prediction modes in hevc
R. Song, D. Liu, H. Li, and F. Wu · 2017
Cited alongside, same era.
Lossy image compression with compressive autoencoders
L. Theis, W. Shi, A. Cunningham, and F. Huszár · 2017
http://x265.org
x265 hevc encoder / h.265 video codec · 2018
Closest in time.
Generative adversarial networks for extreme learned image compression
E. Agustsson, M. Tschannen, F. Mentzer, R. Timofte, and L. Van Gool · 2018
Closest in time.
Variational image compression with a scale hyperprior
J. Ballé, D. Minnen, S. Singh, S. J. Hwang, and N. Johnston · 2018
Closest in time.
Learning for video compression
Z. Chen, T. He, X. Jin, and F. Wu · 2018
Closest in time.
Liteflownet: A lightweight convolutional neural network for optical flow estimation
T.-W. Hui, X. Tang, and C. Change Loy · 2018
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
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
Cited alongside, same era.
Video enhancement with task-oriented flow
T. Xue, B. Chen, J. Wu, D. Wei, and W. T. Freeman · 2017
Cited alongside, same era.
http://bellard.org/bpg/
F. bellard, bpg image format · 2018
Cited alongside, same era.
http://iphome.hhi.de/suehring/
The h.264/avc reference software · 2018
Cited alongside, same era.
https://hevc.hhi.fraunhofer.de/HM-doc/
Hevc test model (hm) · 2018
Cited alongside, same era.
http://ultravideo.cs.tut.fi
Ultra video group test sequences · 2018
Cited alongside, same era.
Improved lossy image compression with priming and spatially adaptive bit rates for recurrent networks
N. Johnston, D. Vincent, D. Minnen, M. Covell, S. Singh, T. Chinen, S. Jin Hwang, J. Shor, and G. Toderici · 2018
Closest in time.
Learning convolutional networks for content-weighted image compression
M. Li, W. Zuo, S. Gu, D. Zhao, and D. Zhang · 2018
Closest in time.
Deep kalman filtering network for video compression artifact reduction
G. Lu, W. Ouyang, D. Xu, X. Zhang, Z. Gao, and M.-T. Sun · 2018
Closest in time.
Conditional probability models for deep image compression
F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, and L. Van Gool · 2018
Closest in time.
Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
D. Sun, X. Yang, M.-Y. Liu, and J. Kautz · 2018
Closest in time.
Learning binary residual representations for domain-specific video streaming
Y.-H. Tsai, M.-Y. Liu, D. Sun, M.-H. Yang, and J. Kautz · 2018
Closest in time.
Video compression through image interpolation
C.-Y. Wu, N. Singhal, and P. Krahenbuhl · 2018
Closest in time.
Compressed video action recognition
C.-Y. Wu, M. Zaheer, H. Hu, R. Manmatha, A. J. Smola, and P. Krähenbühl · 2018
Closest in time.
A lightweight optical flow cnn–revisiting data fidelity and regularization
T.-W. Hui, X. Tang, and C. C. Loy · 2019
Closest in time.