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References

A curated collection of research papers and resources on learned/neural image compression.

Foundational Papers

These papers established the core architectures and techniques used in modern learned image compression.

Paper Authors Venue Links
End-to-end Optimized Image Compression Ballé, Laparra, Simoncelli ICLR 2017 arXiv
Variational Image Compression with a Scale Hyperprior Ballé et al. ICLR 2018 arXiv
Joint Autoregressive and Hierarchical Priors for Learned Image Compression Minnen, Ballé, Toderici NeurIPS 2018 arXiv | GitHub
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules Cheng et al. CVPR 2020 arXiv | GitHub

Transformer-Based Methods

Paper Authors Venue Links
Transformer-based Transform Coding (SwinT-ChARM) Zhu et al. ICLR 2022 OpenReview | GitHub
Entroformer: A Transformer-based Entropy Model for Learned Image Compression Qian et al. ICLR 2022 OpenReview
Transformer-based Image Compression Lu et al. DCC 2022 arXiv | GitHub
Learned Image Compression with Mixed Transformer-CNN Architectures Liu et al. CVPR 2023 CVF | GitHub

Generative Methods (GAN / Diffusion)

Paper Authors Venue Links
High-Fidelity Generative Image Compression (HiFiC) Mentzer et al. NeurIPS 2020 Project | PDF
Lossy Image Compression with Conditional Diffusion Models (CDC) Yang et al. NeurIPS 2023 arXiv | GitHub

Recent Advances (2024-2025)

Paper Venue Links
Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity 2024 arXiv
On Efficient Neural Network Architectures for Image Compression 2024 arXiv
Causal Context Adjustment Loss for Learned Image Compression NeurIPS 2024 GitHub
EVC: Towards Real-Time Neural Image Compression with Mask Decay 2023 arXiv
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model ECCV 2024 GitHub
Enhanced Invertible Encoding for Learned Image Compression (InvCompress) ACM MM 2021 GitHub

Key Libraries & Frameworks

Library Description Links
Tinify PyTorch library and evaluation platform for end-to-end compression research (InterDigital) GitHub | Docs
tensorflow/compression TensorFlow library for learned compression GitHub
Tinify-Trainer Training platform for end-to-end compression models GitHub

Paper Collections & Resources

Repository Description
Awesome-Deep-Compression Paper list of deep learning based image/video compression
Deep-Learning-Based-Image-Compression Paper list about deep learning based image compression
Learned-Image-Video-Compression Collection of papers related to data compression
Image-Compression-Papers-and-Code Papers with code implementations

Review Papers

Paper Links
Image and Video Compression with Neural Networks: A Review arXiv
Deep Architectures for Image Compression: A Critical Review ScienceDirect
Information Compression in the AI Era: Recent Advances and Future Challenges arXiv

Citing Tinify

@article{begaint2020tinify,
    title={Tinify: a PyTorch library and evaluation platform for end-to-end compression research},
    author={B{\'e}gaint, Jean and Racap{\'e}, Fabien and Feltman, Simon and Pushparaja, Akshay},
    year={2020},
    journal={arXiv preprint arXiv:2011.03029},
}

For variable bitrate models:

@article{kamisli2024dcc_vbrlic,
    title={Variable-Rate Learned Image Compression with Multi-Objective Optimization and Quantization-Reconstruction Offsets},
    author={Kamisli, Fatih and Racap{\'e}, Fabien and Choi, Hyomin},
    year={2024},
    booktitle={2024 Data Compression Conference (DCC)},
    eprint={2402.18930},
}