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We introduce a modality-agnostic neural compression algorithm based on a functional view of data and parameterised as an Implicit Neural Representation (INR).
The jpeg still picture compression standard
Wallace, G. K · 1992
Earlier work this paper cites.
MP3 codec
MP3 · 1993
Earlier work this paper cites.
Theoretical foundations of transform coding
Goyal, V. K · 2001
Earlier work this paper cites.
The jpeg 2000 still image compression standard
Skodras, A., Christopoulos, C., and Ebrahimi, T · 2001
Earlier work this paper cites.
Multiscale structural similarity for image quality assessment
Wang, Z., Simoncelli, E. P., and Bovik, A. C · 2003
Earlier work this paper cites.
Overview of the h. 264/avc video coding standard
Wiegand, T., Sullivan, G. J., Bjontegaard, G., and Luthra, A · 2003
Earlier work this paper cites.
Data compression: the complete reference
Salomon, D · 2004
Earlier work this paper cites.
Visualizing data using t-sne
Maaten, L. v. d. and Hinton, G · 2008
Earlier work this paper cites.
Visualizing data using t-sne
Van der Maaten, L. and Hinton, G · 2008
Earlier work this paper cites.
Learning multiple layers of features from tiny images, 2009
Krizhevsky, A. et al · 2009
Earlier work this paper cites.
UCF101: A dataset of 101 human actions classes from videos in the wild
Soomro, K., Zamir, A. R., and Shah, M · 2012
Earlier work this paper cites.
Bpg image format
Bellard, F · 2014
Earlier work this paper cites.
Density modeling of images using a generalized normalization transformation
Ballé, J., Laparra, V., and Simoncelli, E. P · 2015
Earlier work this paper cites.
Shapenet: An information-rich 3d model repository
Chang, A. X., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., et al · 2015
Earlier work this paper cites.
Librispeech: an asr corpus based on public domain audio books
Panayotov, V., Chen, G., Povey, D., and Khudanpur, S · 2015
Earlier work this paper cites.
Empirical evaluation of rectified activations in convolutional network
Xu, B., Wang, N., Chen, T., and Li, M · 2015
Earlier work this paper cites.
Ba, J. L., Kiros, J. R., and Hinton, G. E · 2016
Earlier work this paper cites.
Ntire 2017 challenge on single image super-resolution: Dataset and study
Agustsson, E. and Timofte, R · 2017
Earlier work this paper cites.
End-to-end optimized image compression
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Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks
Finn, C., Abbeel, P., and Levine, S · 2017
Earlier work this paper cites.
Self-normalizing neural networks
Klambauer, G., Unterthiner, T., Mayr, A., and Hochreiter, S · 2017
Earlier work this paper cites.
Meta-sgd: Learning to learn quickly for few-shot learning
Li, Z., Zhou, F., Chen, F., and Li, H · 2017
Earlier work this paper cites.
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Theis, L., Shi, W., Cunningham, A., and Huszár, F · 2017
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Variational image compression with a scale hyperprior
Ballé, J., Minnen, D., Singh, S., Hwang, S. J., and Johnston, N · 2018
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Frankle, J. and Carbin, M · 2018
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Chen, Y., Liu, S., and Wang, X · 2021
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Modulated periodic activations for generalizable local functional representations
Mehta, I., Gharbi, M., Barnes, C., Shechtman, E., Ramamoorthi, R., and Chandraker, M · 2021
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Powerpropagation: A sparsity inducing weight reparameterisation
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Learned initializations for optimizing coordinate-based neural representations
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Generalised implicit neural representations
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Cool-chic: Coordinate-based low complexity hierarchical image codec
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Implicit neural representations for image compression
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Lossy compression with gaussian diffusion
Theis, L., Salimans, T., Hoffman, M. D., and Mentzer, F · 2022
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An introduction to neural data compression
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Generating videos with dynamics-aware implicit generative adversarial networks
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On quantizing implicit neural representations
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