Exploiting Latent Properties to Optimize Neural Codecs | Paper Citation Record

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This paper cites Video compression with rate-distortion autoencoders,.

Exploiting Latent Properties to Optimize Neural Codecs Video compression with rate-distortion autoencoders,

Reference 1

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Observation 1dd62567-8109-4cfc-9dd5-1ade02ef959d · outbound

This paper cites Rethinking lossy compression: The rate- distortion-perception tradeoff,.

Exploiting Latent Properties to Optimize Neural Codecs Rethinking lossy compression: The rate- distortion-perception tradeoff,

Reference 2

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This paper cites Auto-Encoding Variational Bayes.

Exploiting Latent Properties to Optimize Neural Codecs Auto-Encoding Variational Bayes

Reference 3

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This paper cites Lossy Image Compression with Compressive Autoencoders.

Exploiting Latent Properties to Optimize Neural Codecs Lossy Image Compression with Compressive Autoencoders

Reference 4

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This paper cites End-to-end Optimized Image Compression.

Exploiting Latent Properties to Optimize Neural Codecs End-to-end Optimized Image Compression

Reference 5

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This paper cites Variational image compression with a scale hyperprior.

Exploiting Latent Properties to Optimize Neural Codecs Variational image compression with a scale hyperprior

Reference 6

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Observation 7e379d76-f159-4187-a2ae-84398a47b2d2 · outbound

This paper cites Joint autoregressive and hier- archical priors for learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Joint autoregressive and hier- archical priors for learned image compression,

Reference 7

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This paper cites Channel-wise autoregressive entropy models for learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Channel-wise autoregressive entropy models for learned image compression,

Reference 8

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This paper cites Learned image com- pression with discretized gaussian mixture likelihoods and attention modules,.

Exploiting Latent Properties to Optimize Neural Codecs Learned image com- pression with discretized gaussian mixture likelihoods and attention modules,

Reference 9

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Observation cd066ab0-705d-4ee5-a8bb-34a4343e0d59 · outbound

This paper cites Enhanced invertible encoding for learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Enhanced invertible encoding for learned image compression,

Reference 10

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This paper cites Checkerboard context model for efficient learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Checkerboard context model for efficient learned image compression,

Reference 11

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Observation c60ea948-733d-4279-b892-1ce3b13e378e · outbound

This paper cites Learning Accurate Entropy Model with Global Reference for Image Compression.

Exploiting Latent Properties to Optimize Neural Codecs Learning Accurate Entropy Model with Global Reference for Image Compression

Reference 12

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Observation 346509ed-e0b5-467b-88a8-8bb63c1fe2ee · outbound

This paper cites Joint global and local hierarchical priors for learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Joint global and local hierarchical priors for learned image compression,

Reference 13

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Observation 696bdc88-4dde-4f97-8d9b-36357f09b4b6 · outbound

This paper cites Learned image compression with mixed transformer-cnn architectures,.

Exploiting Latent Properties to Optimize Neural Codecs Learned image compression with mixed transformer-cnn architectures,

Reference 14

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Observation dd3c0b68-aaca-4e14-bb12-c74c7da40601 · outbound

This paper cites Dvc: An end-to-end deep video compression framework,.

Exploiting Latent Properties to Optimize Neural Codecs Dvc: An end-to-end deep video compression framework,

Reference 15

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This paper cites Scale-space flow for end-to-end optimized video compres- sion,.

Exploiting Latent Properties to Optimize Neural Codecs Scale-space flow for end-to-end optimized video compres- sion,

Reference 16

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This paper cites AIVC: Artificial Intelligence based Video Codec.

Exploiting Latent Properties to Optimize Neural Codecs AIVC: Artificial Intelligence based Video Codec

Reference 17

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Observation 0a87de39-7fc9-47c7-bbaa-273d5db67621 · outbound

This paper cites End-to-end rate-distortion optimized learned hierarchical bi-directional video compression,.

Exploiting Latent Properties to Optimize Neural Codecs End-to-end rate-distortion optimized learned hierarchical bi-directional video compression,

Reference 18

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Observation cb687e4a-2a5e-4311-87ca-701cc04b1ac3 · outbound

This paper cites Extending neural p-frame codecs for b-frame coding,.

Exploiting Latent Properties to Optimize Neural Codecs Extending neural p-frame codecs for b-frame coding,

Reference 19

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This paper cites Deep contextual video compression,.

Exploiting Latent Properties to Optimize Neural Codecs Deep contextual video compression,

Reference 20

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This paper cites Hybrid spatial-temporal entropy modelling for neural video compression,.

Exploiting Latent Properties to Optimize Neural Codecs Hybrid spatial-temporal entropy modelling for neural video compression,

Reference 21

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This paper cites Gersho and R.

Exploiting Latent Properties to Optimize Neural Codecs Gersho and R

Reference 22

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This paper cites Soft-to-hard vector quantization for end- to-end learning compressible representations,.

Exploiting Latent Properties to Optimize Neural Codecs Soft-to-hard vector quantization for end- to-end learning compressible representations,

Reference 23

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Observation 51a8dc2c-2609-4a06-a7fd-eb55cf819ea9 · outbound

This paper cites Unified multivariate gaussian mixture for efficient neural image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Unified multivariate gaussian mixture for efficient neural image compression,

Reference 24

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This paper cites Nvtc: Nonlinear vector transform coding,.

Exploiting Latent Properties to Optimize Neural Codecs Nvtc: Nonlinear vector transform coding,

Reference 25

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This paper cites LVQ-V AE:end-to- end hyperprior-based variational image compression with lattice vector quantization,.

Exploiting Latent Properties to Optimize Neural Codecs LVQ-V AE:end-to- end hyperprior-based variational image compression with lattice vector quantization,

Reference 26

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This paper cites Lvqac: Lattice vector quantization coupled with spatially adaptive companding for efficient learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Lvqac: Lattice vector quantization coupled with spatially adaptive companding for efficient learned image compression,

Reference 27

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Observation 5f4d2253-6a79-4b29-8cb7-8af68c488e6e · outbound

This paper cites Reducing the amortization gap of entropy bottleneck in end-to-end image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Reducing the amortization gap of entropy bottleneck in end-to-end image compression,

Reference 28

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Observation 7c3470cc-1d0f-4c75-b13a-5bc34f1a144a · outbound

This paper cites Improving inference for neural image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Improving inference for neural image compression,

Reference 29

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Observation 4548599e-7fa0-4252-abf1-efccfe4ae5d1 · outbound

This paper cites Soft then hard: Rethinking the quantization in neural image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Soft then hard: Rethinking the quantization in neural image compression,

Reference 30

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This paper cites Content adaptive optimization for neural image compression,.

Exploiting Latent Properties to Optimize Neural Codecs Content adaptive optimization for neural image compression,

Reference 31

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This paper cites Content adaptive and error propagation aware deep video compression,.

Exploiting Latent Properties to Optimize Neural Codecs Content adaptive and error propagation aware deep video compression,

Reference 32

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This paper cites Overfitting for Fun and Profit: Instance-Adaptive Data Compression.

Exploiting Latent Properties to Optimize Neural Codecs Overfitting for Fun and Profit: Instance-Adaptive Data Compression

Reference 33

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This paper cites Latent-shift: Gradient of entropy helps neural codecs,.

Exploiting Latent Properties to Optimize Neural Codecs Latent-shift: Gradient of entropy helps neural codecs,

Reference 34

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This paper cites Ee2-4.1: Shifting quantization center,.

Exploiting Latent Properties to Optimize Neural Codecs Ee2-4.1: Shifting quantization center,

Reference 35

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This paper cites Asymmetric numeral systems.

Exploiting Latent Properties to Optimize Neural Codecs Asymmetric numeral systems

Reference 36

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This paper cites Universally quantized neural compression,.

Exploiting Latent Properties to Optimize Neural Codecs Universally quantized neural compression,

Reference 37

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This paper cites Optimum quantizer performance for a class of non-gaussian memoryless sources,.

Exploiting Latent Properties to Optimize Neural Codecs Optimum quantizer performance for a class of non-gaussian memoryless sources,

Reference 38

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This paper cites Spectra of quantized signals,.

Exploiting Latent Properties to Optimize Neural Codecs Spectra of quantized signals,

Reference 39

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This paper cites Video coding using learned latent gan compression,.

Exploiting Latent Properties to Optimize Neural Codecs Video coding using learned latent gan compression,

Reference 40

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This paper cites Nonlinear transform coding,.

Exploiting Latent Properties to Optimize Neural Codecs Nonlinear transform coding,

Reference 41

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This paper cites On the structure of vector quantizers,.

Exploiting Latent Properties to Optimize Neural Codecs On the structure of vector quantizers,

Reference 42

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This paper cites Asymptotically optimal block quantization,.

Exploiting Latent Properties to Optimize Neural Codecs Asymptotically optimal block quantization,

Reference 43

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Observation a2bc12a9-7dd1-47be-9444-43dd3d72a9e1 · outbound

This paper cites On the computation of integrals of bivariate gaussian distribution,.

Exploiting Latent Properties to Optimize Neural Codecs On the computation of integrals of bivariate gaussian distribution,

Reference 44

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This paper cites Miettinen, Nonlinear multiobjective optimization.

Exploiting Latent Properties to Optimize Neural Codecs Miettinen, Nonlinear multiobjective optimization

Reference 45

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Observation 5c49ab8c-631d-4e04-a4b9-97d9e9c5faab · outbound

This paper cites Multiple-gradient descent algorithm (mgda) for multi- objective optimization,.

Exploiting Latent Properties to Optimize Neural Codecs Multiple-gradient descent algorithm (mgda) for multi- objective optimization,

Reference 46

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Observation 7f86bc80-ac1d-4b2b-a038-e6b6fc4aebef · outbound

This paper cites CompressAI: a PyTorch library and evaluation platform for end-to-end compression research.

Exploiting Latent Properties to Optimize Neural Codecs CompressAI: a PyTorch library and evaluation platform for end-to-end compression research

Reference 47

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This paper cites Kodak Lossless True Color Image Suite (PhotoCD PCD0992).

Exploiting Latent Properties to Optimize Neural Codecs Kodak Lossless True Color Image Suite (PhotoCD PCD0992)

Reference 48

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Observation d6246ca6-0b4d-42d6-813f-1f286532163e · outbound

This paper cites CLIC: Challenge on learned image compression,.

Exploiting Latent Properties to Optimize Neural Codecs CLIC: Challenge on learned image compression,

Reference 49

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This paper cites Uvg dataset: 50/120fps 4k sequences for video codec analysis and development,.

Exploiting Latent Properties to Optimize Neural Codecs Uvg dataset: 50/120fps 4k sequences for video codec analysis and development,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:39:15.318976Z

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Observation fa7f75c1-06b2-4f93-aa99-d45271c59fa0 · outbound

This paper cites Calculation of average psnr differences between rd curves,.

Exploiting Latent Properties to Optimize Neural Codecs Calculation of average psnr differences between rd curves,

Reference 51

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Observation 4e1bea91-f2a6-4f9e-924c-4630f346c54f · outbound

This paper cites Common test conditions and evaluation procedures for enhanced compression tool testing,.

Exploiting Latent Properties to Optimize Neural Codecs Common test conditions and evaluation procedures for enhanced compression tool testing,

Reference 52

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Observation 9af8f3d2-276d-4bcc-ae5f-a06d75bb1349 · outbound

This paper cites Closest point search in lattices,.

Exploiting Latent Properties to Optimize Neural Codecs Closest point search in lattices,

Reference 53

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This paper cites Fast quantizing and decoding and algorithms for lattice quantizers and codes,.

Exploiting Latent Properties to Optimize Neural Codecs Fast quantizing and decoding and algorithms for lattice quantizers and codes,

Reference 54

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Observation ea79ea48-a841-44c8-ab56-93c7f4e11ccd · outbound

This paper cites Algorithm description of enhanced compression model 9 (ecm 9),.

Exploiting Latent Properties to Optimize Neural Codecs Algorithm description of enhanced compression model 9 (ecm 9),

Reference 55

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Observation df2e7bf4-be23-480c-8b0b-f3b47cf6c4fe · outbound

This paper cites Multilayer feedforward networks are universal approximators,.

Exploiting Latent Properties to Optimize Neural Codecs Multilayer feedforward networks are universal approximators,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:39:15.252212Z

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Observation 588a4a9c-5e6b-47c1-9f0e-29ef7116a979 · outbound

This paper cites an unresolved cited work.

Exploiting Latent Properties to Optimize Neural Codecs Unresolved cited work

Reference 2013

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:39:15.226861Z

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Observation e9145121-c5d5-4b09-8f57-c5cb5db09242 · outbound

This paper cites In 2015-2020, he was a post-doctoral researcher with IRISA, Universite Bre- tagne Sud.

Exploiting Latent Properties to Optimize Neural Codecs In 2015-2020, he was a post-doctoral researcher with IRISA, Universite Bre- tagne Sud

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:39:15.239632Z

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Observation 786887d4-e135-46b4-af5c-fee463cfd5e1 · outbound

This paper cites He is currently working as a principal scientist in video compression at InterDigital Inc.

Exploiting Latent Properties to Optimize Neural Codecs He is currently working as a principal scientist in video compression at InterDigital Inc

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:39:15.212994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Pith citing papers