Awesome End-to-End Neural Image Coding

This repository accompanies the survey End-to-End Neural Image Coding: Foundation, Evolution, Deployment, and Outlook.

The page first highlights the TinyLIC benchmark, then lists papers by survey section.

Figure 2. Core technique taxonomy for end-to-end learned image coding

Figure 8. TinyLIC benchmark overview

00 | Table of Contents

• TinyLIC and Benchmark
• Core Framework
  • Transform
  • Quantization
  • Entropy Modeling
  • Rate-Distortion Optimization
• Practical Extensions
  • Variable-Rate Coding and Rate Control
  • Model Quantization and Cross-Platform Consistence
  • Model Robustness
  • Lightweight Deployment
  • Standardization Progress
• Citation
• Contributing

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01 | TinyLIC and Benchmark

Code links point to confirmed public repositories when available; otherwise - indicates that no reliable open-source implementation was found during this pass.

TinyLIC is the open benchmark centerpiece of this survey: a transparent, efficient, and extensible reference codec for studying practical learned image compression.

1.1 | TinyLIC Design

Component	Description
Backbone	Lightweight VAE-based transform coding framework
Main block	Efficient depth-wise ConvNeXt-style EDN block
Entropy model	Lightweight 4-step channel autoregressive Gaussian model
Complexity levels	Nano, Small, and Base at roughly 10, 20, and 50 KMACs/pixel
Optimization	Objective Fidelity-oriented and Perceptual Realism-oriented variants
Practical tools	Variable-rate control, INT8 consistent decoding, attack-resilient training, progressive coding, and loss-resilient coding

1.2 | TinyLIC Results

TinyLIC Variant	Dec. KMACs/pixel	Params	Kodak PSNR BD-rate vs. VTM	CLIC PSNR BD-rate vs. VTM	Tecnick PSNR BD-rate vs. VTM
Nano	10	3.16M	14.78	14.68	12.76
Small	20	4.76M	5.43	4.63	2.73
Base	50	10.57M	-0.79	-1.76	-4.21
+ VR	50	-	-1.50	-2.75	-5.02
+ VR + INT8	50	-	-0.41	-1.45	-3.68
+ VR + INT8 + Progressive	50	-	3.15	-1.04	-1.71
+ VR + INT8 + Attack-Resilient	50	-	-0.20	-1.36	-3.36
+ VR + INT8 + Loss-Resilient	50	-	9.69	8.54	6.01

Lower BD-rate is better. VTM 22.0 is used as the anchor for distortion-oriented evaluation.

1.3 | Benchmark and Evaluation

Method	Pub.	Arch.	Context	Params	KMACs/pixel	BD-rate vs. VTM	Article	Code
Factorized	ICLR 2017	CNN	Factorized	7.03M	204.00	67.80	Article	GitHub
Hyperprior	ICLR 2018	CNN	Hyperprior	11.81M	208.97	30.14	Article	GitHub
JointAR	NeurIPS 2018	CNN	SAR	25.50M	224.80	10.61	Article	GitHub
ChannelAR	ICIP 2020	CNN	CAR	28.72M	243.00	7.22	Article	GitHub
NLAIC	TIP 2021	Attention	SCAR	65.50M	823.54	5.92	Article	GitHub
GMM	CVPR 2020	CNN	SAR	29.63M	512.80	4.55	Article	GitHub
ELIC	CVPR 2022	CNN	SCAR	36.93M	573.88	-3.22	Article	Github
TIC	DCC 2022	Attention	SCAR	28.40M	506.72	-4.58	Article	GitHub
TCM	CVPR 2023	Attention	CAR	76.57M	1823.58	-10.70	Article	GitHub
QARV	TPAMI 2024	CNN	HAR	93.40M	718.96	-5.81	Article	GitHub
FLIC	ICLR 2024	Attention	CAR	70.97M	1096.04	-12.97	Article	GitHub
MambaIC	CVPR 2025	Mamba	SCAR	75.78M	1284.86	-15.72	Article	GitHub
HPCM	ICCV 2025	CNN	HAR	89.71M	1261.29	-19.19	Article	GitHub
DHIC	ICLR 2026	CNN	HAR	106.93M	977.73	-19.73	Article	GitHub

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02 | Core Framework

2.1 | Transform

2.1.1 | Convolutional Transforms

Paper	Venue	Review Note	Article	Code
End-to-end optimization of nonlinear transform codes for perceptual quality	PCS 2016	Early nonlinear transform coding framework	Article	GitHub
End-to-end optimized image compression	ICLR 2017	Foundational variational transform coding with differentiable quantization surrogate	Article	GitHub
Lossy Image Compression with Compressive Autoencoders	ICLR 2017	Learned autoencoder-based lossy compression	Article	Github
Variational image compression with a scale hyperprior	ICLR 2018	Hyperprior becomes a standard side-information design	Article	GitHub
An End-to-End Compression Framework Based on Convolutional Neural Networks	TCSVT 2018	CNN codec with end-to-end optimization	IEEE	-
Learned Image Compression With Discretized Gaussian Mixture Likelihoods and Attention Modules	CVPR 2020	GMM likelihood and attention-enhanced CNN transform	Article	GitHub
End-to-End Learnt Image Compression via Non-Local Attention Optimization and Improved Context Modeling	TIP 2021	Non-local attention as a bridge from CNNs to global-context codecs	Article	GitHub

2.1.2 | Transformer-Based Transforms

Paper	Venue	Review Note	Article	Code
Transformer-based transform coding	ICLR 2022	Early Transformer transform for image compression	Article	Github
Transformer-based Image Compression	DCC 2022	Transformer image compression	Article	GitHub
Entroformer: A Transformer-based Entropy Model for Learned Image Compression	ICLR 2022	Transformer-based entropy modeling	Article	GitHub
The Devil Is in the Details: Window-based Attention for Image Compression	CVPR 2022	Window attention improves practicality over full attention	Article	GitHub
Contextformer: A Transformer With Spatio-Channel Attention for Context Modeling	ECCV 2022	Spatio-channel attention for context modeling	Article	-
Learned Image Compression With Mixed Transformer-CNN Architectures	CVPR 2023	Hybrid CNN-Transformer design balances local and global modeling	Article	GitHub
Frequency-Aware Transformer for Learned Image Compression	ICLR 2024	Frequency-aware attention and channel-wise autoregressive modeling	Article	GitHub
Linear Attention Modeling for Learned Image Compression	CVPR 2025	Linear-complexity attention for LIC	Article	GitHub

2.1.3 | Mamba-Based Transforms

Paper	Venue	Review Note	Article	Code
MambaVC: Learned Visual Compression with Selective State Spaces	arXiv 2024	Selective state-space modeling for visual compression	Article	GitHub
MambaIC: State Space Models for High-Performance Learned Image Compression	CVPR 2025	SSM-based transform/context modeling for efficient compression	Article	GitHub
CASSIC: Towards Content-Adaptive State-Space Models for Learned Image Compression	ICCV 2025	Content-adaptive state-space codec	Article	-
Content-Aware Mamba for Learned Image Compression	ICLR 2026	Content-aware Mamba transform for LIC	Article	GitHub

2.1.4 | Hierarchical and Alternative Transforms

Paper	Venue	Review Note	Article	Code
Neural Multi-Scale Image Compression	ACCV 2018	Multi-scale learned compression	Article	GitHub
Efficient Variable Rate Image Compression with Multi-Scale Decomposition Network	TCSVT 2018	Multi-scale decomposition for rate scalability	Article	-
Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression	AAAI 2020	Coarse-to-fine hyperprior modeling	Article	GitHub
End-to-End Optimized Versatile Image Compression With Wavelet-Like Transform	TPAMI 2020	Learned wavelet-like transform	Article	GitHub
Graph-Convolution Network for Image Compression	ICIP 2021	Graph-based transform design	Article	-
Lossy Image Compression with Quantized Hierarchical VAEs	WACV 2023	Hierarchical VAE and quantized residual layers	Article	GitHub
QARV: Quantization-Aware ResNet VAE for Lossy Image Compression	TPAMI 2024	Hierarchical residual VAE with quantization-aware design	Article	GitHub
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model	ECCV 2024	Wavelet-domain convolution and entropy modeling	Article	GitHub
FDNet: Frequency Decomposition Network for Learned Image Compression	TCSVT 2024	Frequency decomposition network	Article	-
Taming Hierarchical Image Coding Optimization: A Spectral Regularization Perspective	ICLR 2026	Spectral regularization for hierarchical coding	Article	GitHub
Adaptive Learned Image Compression with Graph Neural Networks	CVPR 2026	Content-adaptive image compression framework based on Graph Neural Networks	Article	GitHub

2.2 | Quantization

Function	Paper	Venue	Review Note	Article	Code
Additive noise surrogate	End-to-end optimized image compression	ICLR 2017	Uniform noise approximates scalar quantization during training	Article	GitHub
Universal quantization	Variable Rate Deep Image Compression With a Conditional Autoencoder	ICCV 2019	Subtractive dithering and conditional autoencoder for rate variation	CVF	-
Soft-to-hard quantization	Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations	NeurIPS 2017	Temperature-controlled relaxation of hard assignments	Proceedings	-
Soft-then-hard quantization	Soft then Hard: Rethinking the Quantization in Neural Image Compression	ICML 2021	Soft training followed by hard quantization finetuning	PMLR	-
Product quantization	NVTC: Nonlinear Vector Transform Coding	CVPR 2023	Hierarchical/product quantization for learned compression	Article	GitHub
Lattice VQ	LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding	CVPR 2023	Lattice VQ with adaptive companding	CVF	-
Adaptive lattice VQ	Multirate Neural Image Compression with Adaptive Lattice Vector Quantization	CVPR 2025	Multirate adaptive lattice VQ	Article	-
Dead-zone quantization	Learned Progressive Image Compression with Dead-zone Quantizers	TCSVT 2022	Sparse-latent quantization with larger zero interval	Article	-
Contextual sequential quantization	NLIC: Non-uniform Quantization-based Learned Image Compression	2024	Context-adaptive quantization levels	Article	-
RD-aware VQ	Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression	CVPR 2026	Differentiable relaxation couples VQ with entropy/R-D loss	Article	GitHub

2.3 | Entropy Modeling

Model Family	Paper	Venue	Review Note	Article	Code
Factorized prior	End-to-end optimized image compression	ICLR 2017	Independent latent prior baseline	Article	GitHub
Hyperprior	Variational image compression with a scale hyperprior	ICLR 2018	Side information predicts latent scale	Article	GitHub
Spatial autoregression	Joint Autoregressive and Hierarchical Priors for Learned Image Compression	NeurIPS 2018	Combines masked spatial context and hyperprior	Article	GitHub
Context-adaptive entropy model	Context-adaptive Entropy Model for End-to-end Optimized Image Compression	ICLR 2019	Adaptive entropy estimation	Article	GitHub
Channel autoregression	Channel-wise Autoregressive Entropy Models for Learned Image Compression	ICIP 2020	Channel dependencies reduce spatial sequential cost	Article	GitHub
Spatial-channel context	Spatial-Channel Context-Based Entropy Modeling for End-to-end Optimized Image Compression	VCIP 2020	Joint spatial and channel context	Article	-
Checkerboard context	Checkerboard Context Model for Efficient Learned Image Compression	CVPR 2021	Parallel-friendly context modeling	Article	GitHub
Uneven space-channel context	ELIC	CVPR 2022	Unevenly grouped SC context for strong R-D performance	Article	Github
Multi-reference context	MLIC / MLIC++	MM 2023 / TOMM 2025	Multi-reference entropy modeling and linear-complexity extension	Article	GitHub
Hierarchical progressive context	HPCM	ICCV 2025	Multi-scale progressive context schedule	Article	GitHub
Hierarchical VAE	Taming Hierarchical Image Coding Optimization: A Spectral Regularization Perspective	ICLR 2026	Hierarchical modeling	Article	GitHub

2.4 | Rate-Distortion Optimization

Direction	Paper	Venue	Review Note	Article	Code
Perception-distortion theory	The Perception-Distortion Tradeoff	CVPR 2018	Formalizes the perception-distortion frontier	Article	-
Rate-distortion-perception	Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff	ICML 2019	Theoretical R-D-P trade-off	Article	-
Learned perceptual metric	The Unreasonable Effectiveness of Deep Features as a Perceptual Metric	CVPR 2018	LPIPS-style perceptual losses	Article	-
Perceptual/generative compression	High-Fidelity Generative Image Compression	NeurIPS 2020	GAN-based high-fidelity compression	Article	GitHub
Statistical fidelity	Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models	ICML 2023	Implicit local likelihood models improve perceptual statistics	Article	GitHub
Human-machine coding	Icmh-Net: Neural Image Compression towards Both Machine Vision and Human Vision	ACM MM 2023	Neural image compression for human and machine vision	Article	-
Multi-machine coding	All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation	NeurIPS 2024	Neural image compression for multi-tasks	Article	GitHub

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03 | Practical Extensions

3.1 | Variable-Rate Coding and Rate Control

3.1.1 | Variable-Rate Coding

Function	Paper	Venue	Review Note	Article	Code
Recurrent refinement	Variable Rate Image Compression with Recurrent Neural Networks	ICLR 2016	Bitrate controlled by recurrent iteration count	Article	-
Recurrent full-resolution codec	Full Resolution Image Compression with Recurrent Neural Networks	CVPR 2017	RNN residual refinement at full resolution	Article	GitHub
Improved recurrent codec	Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates	CVPR 2018	Better recurrent training and adaptive bit allocation	Article	-
Slimmable codec	Slimmable Compressive Autoencoders for Practical Neural Image Compression	CVPR 2021	Subnetworks represent different rate/complexity levels	Article	GitHub
Quality scaling factor	Variable Bitrate Image Compression with Quality Scaling Factors	ICASSP 2020	Latent scaling controls bitrate in a single model	Article	GitHub
Modulated autoencoder	Variable Rate Deep Image Compression with Modulated Autoencoder	SPL 2020	Modulation controls rate without multiple models	Article	GitHub
Conditional autoencoder	Variable Rate Deep Image Compression with a Conditional Autoencoder	ICCV 2019	Conditional rate control	Article	-
Interpolation VRC	Interpolation Variable Rate Image Compression	ACM MM 2021	Fine-grained rate interpolation	Article	-
Asymmetric gained VRC	Asymmetric Gained Deep Image Compression with Continuous Rate Adaptation	CVPR 2021	Continuous rate adaptation with gained units	Article	GitHub
High-fidelity VRC	High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation	ACM MM 2022	Invertible activation transformation for perceptual VRC	Article	GitHub
Spatial importance guidance	SIGVIC: Spatial Importance Guided Variable-Rate Image Compression	ICASSP 2023	Spatially adaptive bit allocation	Article	GitHub
Transformer ROI control	Transformer-Based Variable-Rate Image Compression with Region-of-Interest Control	ICIP 2023	Transformer VRC with ROI control	Article	GitHub
Adaptive quantization	Stanh: Parametric Quantization for Variable Rate Learned Image Compression	TIP 2025	Parametric quantizer for variable-rate LIC	Article	GitHub

3.1.2 | Progressive Coding

Function	Paper	Venue	Review Note	Article	Code
Recurrent progressive coding	Learning to Inpaint for Image Compression	NeurIPS 2017	Progressive reconstruction with recurrent refinement	Article	-
Selective latent compression	Selective Compression Learning of Latent Representations for Variable-Rate Image Compression	NeurIPS 2022	Selectively transmits latent subsets	Article	GitHub
Trit-plane coding	DPICT: Deep progressive image compression using trit-planes	CVPR 2022	Ordered ternary-plane transmission	Article	GitHub
Intrinsic importance ordering	ProgDTD: Progressive Learned Image Compression With Double-Tail-Drop Training	CVPRW 2023	Training objective encourages latent importance order	Article	GitHub
Efficient progressive coding	Efficient progressive image compression with variance-aware masking	WACV 2025	Element-wise importance ranking and masking	Article	GitHub

3.1.3 | Rate Control

Function	Paper	Venue	Review Note	Article	Code
JPEG AI VRC analysis	Overview of Variable Rate Coding in JPEG AI	TCSVT 2025	Reviews 3D quality control and rate matching	IEEE	-
Rate-feature-level prediction	Rate Controllable Learned Image Compression Based on RFL Model	VCIP 2022	Predicts coding parameters from target rate and image features	Article	-
Lambda-domain RC	Lambda-domain Rate Control for Neural Image Compression	MMAsia 2023	Predicts lambda from target bitrate	Article	-
Neural RC for JPEG AI	An Efficient Neural Rate Control for JPEG-AI	TCSVT 2025	Neural predictor selects discrete model/parameter indices	IEEE	-
Block-level RC	Block-Level Rate Control for Learnt Image Coding	PCS 2022	Block-wise bitrate-parameter curves and greedy allocation	IEEE	-
Accelerated block-level RC	Accelerating Block-level Rate Control for Learned Image Compression	DCC 2024	Predicts block curves from sampled blocks	IEEE	-

3.2 | Model Quantization and Cross-Platform Consistence

3.2.1 | QAT and PTQ

Function	Paper	Venue	Review Note	Article	Code
Integer-only codec	Integer Networks for Data Compression with Latent-Variable Models	ICLR 2019	Eliminates floating-point mismatch through integer-domain design	OpenReview	-
Fixed-point decoding	Efficient Neural Image Decoding via Fixed-Point Inference	TCSVT 2020	Fixed-point inference for deterministic decoding	Article	GitHub
Fixed-point arithmetic	Learned Image Compression with Fixed-Point Arithmetic	PCS 2021	Fixed-point arithmetic for LIC	Article	-
QAT with channel splitting	Q-LIC: Quantizing Learned Image Compression with Channel Splitting	TCSVT 2022	Splits high-error channels to reduce quantization distortion	Article	-
PTQ consistency	Post-Training Quantization for Cross-Platform Learned Image Compression	arXiv 2022	PTQ plus deterministic entropy coding	arXiv	-
R-D optimized PTQ	Rate-Distortion Optimized Post-Training Quantization for Learned Image Compression	TCSVT 2023	Optimizes quantization with compression-aware losses	Article	GitHub

3.2.2 | Mixed-Precision Quantization and Joint Compression

Function	Paper	Venue	Review Note	Article	Code
Mixed precision	Flexible Mixed Precision Quantization for Learned Image Compression	ICME 2024	Assigns different precision to sensitive modules	Article	GitLab
Mixed-precision PTQ	Mixed-Precision Post-Training Quantization for Learned Image Compression	IoT-J 2025	Post-training bit-width allocation	Article	-
Pruning + QAT	Structured Pruning and Quantization for Learned Image Compression	ICIP 2024	Joint model compression for deployment	Article	-

3.3 | Model Robustness

3.3.1 | Attacks

Function	Paper	Venue	Review Note	Article	Code
Manipulation attacks	MALICE: Manipulation Attacks on Learned Image Compression	arXiv 2022	Early attack formulation for learned codecs	arXiv	-
White-box evasion	Toward Robust Neural Image Compression: Adversarial Attack and Model Finetuning	TCSVT 2023	FTDA attack and adversarial finetuning defense	Article	GitHub
Backdoor attack	Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger	CVPR 2023	Poisoned trigger attacks in compression training	Article	-
Robust backdoor trigger	Robust and Transferable Backdoor Attacks Against Deep Image Compression With Selective Frequency Prior	TPAMI 2025	Frequency-domain/robust triggers	Article	-
JPEG AI robustness	Exploring adversarial robustness of JPEG AI: methodology, comparison and new methods	arXiv 2024	Large-scale JPEG AI perturbation/attack evaluation	arXiv	-

3.3.2 | Defenses and Practical Robustness

Function	Paper	Venue	Review Note	Article	Code
Architecture-level simplification	MALICE / manipulation attack follow-ups	2022-2023	Simpler entropy models can reduce attack sensitivity	arXiv	-
Adversarial training	Toward Robust Neural Image Compression	TCSVT 2023	Robust finetuning improves adversarial stability	Article	GitHub
Latent consistency	Successive Learned Image Compression: Comprehensive Analysis of Instability	Neurocomputing 2022	Repeated compression and latent consistency	Article	-
Transmission error robustness	ResiComp: Loss-Resilient Image Compression via Dual-Functional Masked Visual Token Modeling	TCSVT 2025	Joint source-channel style robustness to packet loss	Article	GitHub
Loss-resilient learned compression	Towards Loss-Resilient Image Coding for Unstable Satellite Networks	AAAI 2025	Network-aware training for unreliable channels	Article	GitHub
Compression as defense	ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples	CVPR 2019	Compression model as adversarial defense for vision tasks	Article	GitHub

3.4 | Lightweight Deployment

3.4.1 | Knowledge Distillation

Function	Paper	Venue	Review Note	Article	Code
Output/entropy distillation	Fast and High-Performance Learned Image Compression with Improved Checkerboard Context Model, Deformable Residual Module, and Knowledge Distillation	TIP 2024	Distillation for faster learned codec	Article	-
Efficient LIC distillation	Efficient Learned Image Compression Through Knowledge Distillation	arXiv 2025	Intermediate/latent distillation for smaller students	Article	GitHub
KDIC	Knowledge Distillation for Learned Image Compression	ICCV 2025	Multi-level distillation across codec blocks	Article	-
EVC	EVC: Towards Practical Neural Image Compression	CVPR/TCSVT-era	Mask-decay model slimming from large to small codec	Article	GitHub
CSLIC	Distilling Complexity-Scalable Learned Image Compression Models via Neural Architecture Search	TCSVT 2026	NAS + KD for scalable complexity levels	Article	-

3.4.2 | Architecture-Level Lightweight Design

Function	Paper	Venue	Review Note	Article	Code
Non-autoregressive codec	Towards Efficient Image Compression Without Autoregressive Models	NeurIPS 2023	Removes sequential AR bottleneck	Article	-
Asymmetric codec	AsymLLIC: Asymmetric Lightweight Learned Image Compression	VCIP 2024	Shifts computation to encoder, keeps decoder light	Article	GitHub
Shift operations	ShiftLIC: Lightweight Learned Image Compression with Spatial-Channel Shift Operations	TCSVT 2025	Shift operators replace heavier convolutions	Article	GitHub
Lightweight attention	Towards Real-Time Practical Image Compression with Lightweight Attention	ESWA 2024	Lightweight attention for practical decoding	Article	GitHub
Shallow decoder	Computationally-Efficient Neural Image Compression with Shallow Decoders	ICCV 2023	Nearly linear decoder for low KMAC deployment	Article	GitHub
Switchable priors	Learning Switchable Priors for Neural Image Compression	TCSVT 2025	Low-complexity FastNIC with switchable priors	Article	-
Dynamic routing	AdaNIC: Towards Practical Neural Image Compression via Dynamic Transform Routing	ICCV 2023	Content-aware computation allocation	CVF	GitHub

3.4.3 | Test-Time Adaptation

Function	Paper	Venue	Review Note	Article	Code
Latent refinement	Content Adaptive Optimization for Neural Image Compression	CVPRW 2019	Optimizes latents per image at encoding time	Article	-
Improved latent inference	Improving Inference for Neural Image Compression	NeurIPS 2020	Refines latents and side information	Article	GitHub
Instance-adaptive compression	Overfitting for Fun and Profit: Instance-Adaptive Data Compression	ICLR 2021	Per-instance decoder/entropy optimization	Article	-
Adapter-based adaptation	Dec-Adapter: Exploring Efficient Decoder-Side Adapter for Bridging Screen Content and Natural Image Compression	ICCV 2023	Decoder-side adapters for domain shift	CVF	-
Universal adapters	Universal Deep Image Compression via Content-Adaptive Optimization with Adapters	WACV 2023	Adapter-based content adaptation	CVF	GitHub
Dynamic low-rank adaptation	Dynamic Low-Rank Instance Adaptation for Universal Neural Image Compression	ACM MM 2023	Low-rank adaptation for per-image/domain shifts	Article	GitHub
Cross-domain TTA	Test-Time Adaptation for Image Compression with Distribution Regularization	ICLR 2025	Plug-and-play Bayesian regularization under shifts	Article	GitHub

3.5 | Standardization Progress

Standard / Topic	Paper or Document	Year	Review Note	Article	Code
JPEG AI standard overview	The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption	2023	Early overview of JPEG AI objectives	Article	-
IEEE 1857.11	IEEE Standard for Neural Network-Based Image Coding	2024	Neural network-based image coding standard	Article	-

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04 | Contributing

Pull requests are welcome. Please add new entries under the matching review subsection.

| Function | Paper | Venue | Review Note | Link |

If a paper spans multiple functions, list it in each relevant subsection, following the structure above.