HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models
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Abstract (arXiv)
We make the following striking observation: fully convolutional VAE models trained on 32x32 ImageNet can generalize well, not just to 64x64 but also to far larger photographs, with no changes to the model. We use this property, applying fully convolutional models to lossless compression, demonstrating a method to scale the VAE-based 'Bits-Back with ANS' algorithm for lossless compression to large color photographs, and achieving state of the art for compression of full size ImageNet images. We release Craystack, an open source library for convenient prototyping of lossless compression using probabilistic models, along with full implementations of all of our compression results.
Key facts. Cited by 37 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Dec 2019.
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Citing papers per year: 2021: 15; 2022: 14; 2023: 1; 2024: 3; 2025: 4.
37 papers.
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- 2021Variational Diffusion Modelscited by 1,153
- 2021Autoregressive Diffusion Modelscited by 210
- 2022An Introduction to Neural Data Compressioncited by 79
- 2022Lossy Image Compression with Quantized Hierarchical VAEscited by 35
- 2021On the Out-of-distribution Generalization of Probabilistic Image Modellingcited by 33
- 2023QARV: Quantization-Aware ResNet VAE for Lossy Image Compressioncited by 32
- 2021iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compressioncited by 27
- 2021iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Codercited by 26
- 2022Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compressioncited by 22
- 2021Lossless Compression with Probabilistic Circuitscited by 20
- 2021Improving Lossless Compression Rates via Monte Carlo Bits-Back Codingcited by 19
- 2022RIDDLE: Lidar Data Compression with Range Image Deep Delta Encodingcited by 19
25 more
- 2021Partition and Code: learning how to compress graphscited by 10
- 2022Generalization Gap in Amortized Inferencecited by 10
- 2021IB-DRR: Incremental Learning with Information-Back Discrete Representation Replaycited by 9
- 2021Lossless compression with state space models using bits back codingcited by 6
- 2022Improving VAE-based Representation Learningcited by 6
- 2024CALLIC: Content Adaptive Learning for Lossless Image Compressioncited by 6
- 2021Lossless Image Compression Using a Multi-Scale Progressive Statistical Modelcited by 5
- 2022Split Hierarchical Variational Compressioncited by 5
- 2022PILC: Practical Image Lossless Compression with an End-to-end GPU Oriented Neural Frameworkcited by 5
- 2021Lossless Compression with Latent Variable Modelscited by 4
- 2021Compressing Multisets with Large Alphabets using Bits-Back Codingcited by 4
- 2022Parallel Neural Local Lossless Compressioncited by 4
- 2022Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domaincited by 4
- 2022Fast Lossless Neural Compression with Integer-Only Discrete Flowscited by 4
- 2025Generative Modeling with Bayesian Sample Inferencecited by 4
- 2021Discrete Denoising Flowscited by 2
- 2025LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Imagescited by 2
- 2024Point Cloud Compression with Bits-back Codingcited by 1
- 2025Lossless Compression of Vector IDs for Approximate Nearest Neighbor Searchcited by 1
- 2025SEEC: Segmentation-Assisted Multi-Entropy Models for Learned Lossless Image Compressioncited by 1
- 2021OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compressioncited by 0
- 2022Multi-Scale Architectures Matter: On the Adversarial Robustness of Flow-based Lossless Compressioncited by 0
- 2022GOLLIC: Learning Global Context beyond Patches for Lossless High-Resolution Image Compressioncited by 0
- 2022Verified Reversible Programming for Verified Lossless Compressioncited by 0
- 2024FLLIC: Functionally Lossless Image Compressioncited by 0
- 2025SEEC: Segmentation-Assisted Multi-Entropy Models for Learned Lossless Image Compression9 Sep 2025
- 2025LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images22 Jun 2025
- 2025Generative Modeling with Bayesian Sample Inference11 Feb 2025
- 2025Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search16 Jan 2025
- 2024CALLIC: Content Adaptive Learning for Lossless Image Compression23 Dec 2024
- 2024Point Cloud Compression with Bits-back Coding9 Oct 2024
- 2024FLLIC: Functionally Lossless Image Compression24 Jan 2024
- 2023QARV: Quantization-Aware ResNet VAE for Lossy Image Compression16 Feb 2023
- 2022Verified Reversible Programming for Verified Lossless Compression2 Nov 2022
- 2022GOLLIC: Learning Global Context beyond Patches for Lossless High-Resolution Image Compression7 Oct 2022
- 2022Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression11 Sep 2022
- 2022Lossy Image Compression with Quantized Hierarchical VAEs27 Aug 2022
25 more
- 2022Multi-Scale Architectures Matter: On the Adversarial Robustness of Flow-based Lossless Compression26 Aug 2022
- 2022Fast Lossless Neural Compression with Integer-Only Discrete Flows17 Jun 2022
- 2022PILC: Practical Image Lossless Compression with an End-to-end GPU Oriented Neural Framework10 Jun 2022
- 2022RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding2 Jun 2022
- 2022Improving VAE-based Representation Learning28 May 2022
- 2022Generalization Gap in Amortized Inference23 May 2022
- 2022Split Hierarchical Variational Compression5 Apr 2022
- 2022Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain30 Mar 2022
- 2022An Introduction to Neural Data Compression14 Feb 2022
- 2022Parallel Neural Local Lossless Compression13 Jan 2022
- 2021Lossless Compression with Probabilistic Circuits23 Nov 2021
- 2021OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression2 Nov 2021
- 2021iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder1 Nov 2021
- 2021Autoregressive Diffusion Models5 Oct 2021
- 2021On the Out-of-distribution Generalization of Probabilistic Image Modelling4 Sep 2021
- 2021Lossless Image Compression Using a Multi-Scale Progressive Statistical Model24 Aug 2021
- 2021Discrete Denoising Flows24 Jul 2021
- 2021Compressing Multisets with Large Alphabets using Bits-Back Coding15 Jul 2021
- 2021Partition and Code: learning how to compress graphs5 Jul 2021
- 2021Variational Diffusion Models1 Jul 2021
- 2021IB-DRR: Incremental Learning with Information-Back Discrete Representation Replay21 Apr 2021
- 2021Lossless Compression with Latent Variable Models21 Apr 2021
- 2021iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression30 Mar 2021
- 2021Lossless compression with state space models using bits back coding18 Mar 2021
- 2021Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding22 Feb 2021
- 2021Variational Diffusion Modelscited by 1,153
- 2021Autoregressive Diffusion Modelscited by 210
- 2021Autoregressive Diffusion Models5 Oct 2021
- 2021Variational Diffusion Models1 Jul 2021
- 2022An Introduction to Neural Data Compressioncited by 79
- 2022Lossy Image Compression with Quantized Hierarchical VAEscited by 35
- 2021On the Out-of-distribution Generalization of Probabilistic Image Modellingcited by 33
- 2023QARV: Quantization-Aware ResNet VAE for Lossy Image Compressioncited by 32
- 2021iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compressioncited by 27
- 2021iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Codercited by 26
- 2022Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compressioncited by 22
- 2021Lossless Compression with Probabilistic Circuitscited by 20
- 2021Improving Lossless Compression Rates via Monte Carlo Bits-Back Codingcited by 19
- 2022RIDDLE: Lidar Data Compression with Range Image Deep Delta Encodingcited by 19
- 2021Partition and Code: learning how to compress graphscited by 10
- 2022Generalization Gap in Amortized Inferencecited by 10
12 most cited of 35 All 35 (JSON)
- 2025SEEC: Segmentation-Assisted Multi-Entropy Models for Learned Lossless Image Compression9 Sep 2025
- 2025LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images22 Jun 2025
- 2025Generative Modeling with Bayesian Sample Inference11 Feb 2025
- 2025Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search16 Jan 2025
- 2024CALLIC: Content Adaptive Learning for Lossless Image Compression23 Dec 2024
- 2024Point Cloud Compression with Bits-back Coding9 Oct 2024
- 2024FLLIC: Functionally Lossless Image Compression24 Jan 2024
- 2023QARV: Quantization-Aware ResNet VAE for Lossy Image Compression16 Feb 2023
- 2022Verified Reversible Programming for Verified Lossless Compression2 Nov 2022
- 2022GOLLIC: Learning Global Context beyond Patches for Lossless High-Resolution Image Compression7 Oct 2022
- 2022Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression11 Sep 2022
- 2022Lossy Image Compression with Quantized Hierarchical VAEs27 Aug 2022
12 newest of 35 All 35 (JSON)