Purpose: We aim to provide a summary of neural image compression. More papers will be summarized.
University of Science and Technology of China (USTC), Intelligent Media Computing Lab.
📌 About new works. If you want to incorporate your studies (e.g., the link of paper or project) on neural image compression in this repository. Welcome to raise an issue or email us. We will incorporate it into this repository and our survey report as soon as possible.
- Survey & Benchmark
- Lossless Image Compression
- Near-Lossless Image Compression
- Lossy Image Compression
- Other tasks
| Paper | First Author | Venue |
|---|---|---|
| Learning-driven lossy image compression: A comprehensive survey | Sonain Jamil | Engineering Applications of Artificial Intelligence, 2023 |
| An Introduction to Neural Data Compression | Yibo Yang | Foundations and Trends® in Computer Graphics and Vision, 2023 |
| Learning End-to-End Lossy Image Compression: A Benchmark | Yueyu Hu | TPAMI2022 |
| Deep architectures for image compression: a critical review | Dipti Mishra | Signal Processing, 2022 |
| Image and Video Compression With Neural Networks: A Review | Siwei Ma | TCSVT2019 |
| A comprehensive survey on image encryption: Taxonomy, challenges, and future directions | Morteza SaberiKamarposhti | Chaos, Solitons and Fractals, 2024 |
| Models | Paper | First Author | Architecture | Venue | Project |
|---|---|---|---|---|---|
| -- | Ultra High Fidelity Deep Image Decompression With l∞-Constrained Compression | Xi Zhang | CNN | TIP2020 | |
| -- | Learning Scalable l∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression | Yuanchao Bai | VAE | CVPR2021 |  |
| DLPR | Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression | Yuanchao Bai | VAE | TPAMI2023 |  |
| Models | Paper | First Author | Architecture | Venue | Project |
|---|---|---|---|---|---|
| -- | Learned Image Compression with Mixed Transformer-CNN Architectures | Jinming Liu | AE | CVPR2023 |  |
| NVTC | NVTC: Nonlinear Vector Transform Coding | Runsen Feng | CVPR2023 |  |
|
| ELIC | ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding | Dailan He | CVPR2022 | ||
| SHVQ | Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations | Eirikur Agustsson | AE | NIPS2017 | |
| -- | Lossy Image Compression with Compressive Autoencoders | Lucas Theis | AE | ICLR2017 | |
| -- | End-to-end Optimized Image Compression | Johannes Ballé | AE | ICLR2017 |  |
| -- | Few-Shot Domain Adaptation for Learned Image Compression | Tianyu Zhang | AE | Arxiv2024 |
| Models | Paper | First Author | Architecture | Venue | Project |
|---|---|---|---|---|---|
| CDC | Lossy Image Compression with Conditional Diffusion Models | Ruihan Yang | Diffusion Model | NeurIPS2023 |  |
| HiFiC | High-Fidelity Generative Image Compression | Fabian Mentzer | GAN | NeurIPS2020 | |
| -- | Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff | Yochai Blau | -- | ICML2019 |
| Methods | Paper | First Author | Venue |
|---|---|---|---|
| Visual Cryptography | Dynamic feedback bit‑level image privacy protection based on chaos and information hiding | Jinlong Zhang | scientific Reports, 2024 |
| CS | A multi-level privacy-preserving scheme for extracting traffic images | Xiaofei He | Signal Processing, 2024 |
| DNA | A novel image compression and encryption scheme based on conservative chaotic system and DNA method | Xin Wu | Chaos, Solitons and Fractals, 2023 |
