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Implicit Neural Representations (INR) have recently shown to be powerful tool for high-quality video compression.
Arithmetic coding for data compression
Ian H Witten, Radford M Neal, and John G Cleary · 1987
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The jpeg still picture compression standard
G.K. Wallace · 1992
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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High efficiency video coding (hevc)
Vivienne Sze, Madhukar Budagavi, and Gary J Sullivan · 2014
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Youtube-8m: A large-scale video classification benchmark
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan · 2016
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End-to-end optimized image compression
Johannes Ballé, Valero Laparra, and Eero P Simoncelli · 2016
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Toward A Practical Perceptual Video Quality Metric, 2016
Zhi Li, Anne Aaron, Ioannis Katsavounidis, Anush Moorthy, and Megha Manohara · 2016
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Towards accurate binary convolutional neural network
Xiaofan Lin, Cong Zhao, and Wei Pan · 2017
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Lossy image compression with compressive autoencoders
Lucas Theis, Wenzhe Shi, Andrew Cunningham, and Ferenc Huszár · 2017
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Variational image compression with a scale hyperprior
Johannes Ballé, David Minnen, Saurabh Singh, Sung Jin Hwang, and Nick Johnston · 2018
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An overview of core coding tools in the av1 video codec
Yue Chen, Debargha Murherjee, Jingning Han, Adrian Grange, Yaowu Xu, Zoe Liu, Sarah Parker, Cheng Chen, Hui Su, Urvang Joshi, et al · 2018
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2018
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Joint autoregressive and hierarchical priors for learned image compression
David Minnen, Johannes Ballé, and George D Toderici · 2018
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Clip-q: Deep network compression learning by in-parallel pruning-quantization
Frederick Tung and Greg Mori · 2018
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Stabilizing the lottery ticket hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M Roy, and Michael Carbin · 2019
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The state of sparsity in deep neural networks
Trevor Gale, Erich Elsen, and Sara Hooker · 2019
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And the bit goes down: Revisiting the quantization of neural networks
Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, and Hervé Jégou · 2019
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Learning continuous image representation with local implicit image function
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Training with quantization noise for extreme model compression
Angela Fan, Pierre Stock, Benjamin Graham, Edouard Grave, Rémi Gribonval, Herve Jegou, and Armand Joulin · 2020
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Uvg dataset: 50/120fps 4k sequences for video codec analysis and development
Alexandre Mercat, Marko Viitanen, and Jarno Vanne · 2020
Learned initializations for optimizing coordinate-based neural representations
Matthew Tancik, Ben Mildenhall, Terrance Wang, Divi Schmidt, Pratul P. Srinivasan, Jonathan T. Barron, and Ren Ng · 2021
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On the out-of-distribution generalization of probabilistic image modelling
Mingtian Zhang, Andi Zhang, and Steven McDonagh · 2021
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Implicit neural video compression
Yunfan Zhang, Ties van Rozendaal, Johann Brehmer, Markus Nagel, and Taco Cohen · 2021
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Ps-nerv: Patch-wise stylized neural representations for videos
Yunpeng Bai, Chao Dong, and Cairong Wang · 2022
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Oodhdr-codec: Out-of-distribution generalization for hdr image compression
Linfeng Cao, Aofan Jiang, Wei Li, Huaying Wu, and Nanyang Ye · 2022
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Scalable model compression by entropy penalized reparameterization
D. Oktay et al · 2020
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2020
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Nerv: Neural representations for videos
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Coin: Compression with implicit neural representations
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Multiplicative filter networks
Rizal Fathony, Anit Kumar Sahu, Devin Willmott, and J. Zico Kolter · 2021
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Transformers as meta-learners for implicit neural representations
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Efficient meta-tuning for content-aware neural video delivery
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Residual multiplicative filter networks for multiscale reconstruction
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