mlsanityData to 7 Oct 2026

DPICT: Deep Progressive Image Compression Using Trit-Planes

arXiv 2112.06334 ↗First posted 12 Dec 2021eess.IV cs.CVcited by 25

Not on the map. Why?

Abstract (arXiv)

We propose the deep progressive image compression using trit-planes (DPICT) algorithm, which is the first learning-based codec supporting fine granular scalability (FGS). First, we transform an image into a latent tensor using an analysis network. Then, we represent the latent tensor in ternary digits (trits) and encode it into a compressed bitstream trit-plane by trit-plane in the decreasing order of significance. Moreover, within each trit-plane, we sort the trits according to their rate-distortion priorities and transmit more important information first. Since the compression network is less optimized for the cases of using fewer trit-planes, we develop a postprocessing network for refining reconstructed images at low rates. Experimental results show that DPICT outperforms conventional progressive codecs significantly, while enabling FGS transmission. Codes are available at https://github.com/jaehanlee-mcl/DPICT.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 28 of its 48 references that are in the map. First posted on arXiv 12 Dec 2021.

Builds on

28 of 48 references.

References · 28

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2018Variational image compression with a scale hyperpriorcited by 910
  4. 2016End-to-end Optimized Image Compressioncited by 673
  5. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 642
  6. 2017Video Enhancement with Task-Oriented Flowcited by 612
  7. 2017Snapshot Ensembles: Train 1, get M for freecited by 349
  8. 2018Slimmable Neural Networkscited by 301
  9. 2017Lossy Image Compression with Compressive Autoencoderscited by 289
  10. 2020CompressAI: a PyTorch library and evaluation platform for end-to-end compression researchcited by 271
  11. 2019Universally Slimmable Networks and Improved Training Techniquescited by 219
  12. 2018Generative Adversarial Networks for Extreme Learned Image Compressioncited by 213
16 more
  1. 2016Full Resolution Image Compression with Recurrent Neural Networkscited by 170
  2. 2015Variable Rate Image Compression with Recurrent Neural Networkscited by 168
  3. 2017Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representationscited by 149
  4. 2018Context-adaptive Entropy Model for End-to-end Optimized Image Compressioncited by 138
  5. 2018Conditional Probability Models for Deep Image Compressioncited by 128
  6. 2017Real-Time Adaptive Image Compressioncited by 127
  7. 2019Variable Rate Deep Image Compression With a Conditional Autoencodercited by 109
  8. 2017Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networkscited by 91
  9. 2020Asymmetric Gained Deep Image Compression With Continuous Rate Adaptationcited by 83
  10. 2018Deep Generative Models for Distribution-Preserving Lossy Compressioncited by 59
  11. 2019Variable Rate Deep Image Compression with Modulated Autoencodercited by 39
  12. 2021Slimmable Compressive Autoencoders for Practical Neural Image Compressioncited by 38
  13. 2016Towards Conceptual Compressioncited by 36
  14. 2019Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compressioncited by 33
  15. 2018Neural Multi-scale Image Compressioncited by 10
  16. 2021Image Compression with Recurrent Neural Network and Generalized Divisive Normalizationcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 4; 2024: 5; 2025: 8; 2026: 7.

25 papers.

Sort:

By area:

  1. 2023Context-Based Trit-Plane Coding for Progressive Image Compressioncited by 21
  2. 2024Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptationcited by 15
  3. 2023ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Trainingcited by 13
  4. 2024Progressive Compression with Universally Quantized Diffusion Modelscited by 10
  5. 2025PTQTP: Post-Training Quantization to Trit-Planes for Large Language Modelscited by 9
  6. 2023Real-time 6K Image Rescaling with Rate-distortion Optimizationcited by 6
  7. 2023Exploring Resolution Fields for Scalable Image Compression with Uncertainty Guidancecited by 6
  8. 2024DeepHQ: Learned Hierarchical Quantizer for Progressive Deep Image Codingcited by 5
  9. 2024Efficient Progressive Image Compression with Variance-aware Maskingcited by 4
  10. 2025Remote Inference over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector Quantizationcited by 3
  11. 2022RD-Optimized Trit-Plane Coding of Deep Compressed Image Latent Tensorscited by 2
  12. 2025CANeRV: Content Adaptive Neural Representation for Video Compressioncited by 2
13 more
  1. 2026ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantizationcited by 2
  2. 2024Learned Compression of Point Cloud Geometry and Attributes in a Single Model through Multimodal Rate-Controlcited by 1
  3. 2025LimitNet: Progressive, Content-Aware Image Offloading for Extremely Weak Devices & Networkscited by 1
  4. 2025Progressive Learned Image Compression for Machine Perceptioncited by 1
  5. 2025HCF: Hierarchical Cascade Framework for Distributed Multi-Stage Image Compressioncited by 0
  6. 2025Neural Weight Compression for Language Modelscited by 0
  7. 2025ProDAT: Progressive Density-Aware Tail-Drop for Point Cloud Codingcited by 0
  8. 2026ProGS: Towards Progressive Coding for 3D Gaussian Splattingcited by 0
  9. 2026Joint Degradation-Aware Arbitrary-Scale Super-Resolution for Variable-Rate Extreme Image Compressioncited by 0
  10. 2026Coarse-to-Fine: Progressive Image Compression for Semantically Hierarchical Classificationcited by 0
  11. 2026Proteus: A Truncation-Robust Entropy Model for Progressive LiDAR Compressioncited by 0
  12. 2026Every Packet Counts: Dispersing Information for Loss-Resilient Learned Image Compressioncited by 0
  13. 2026Tree-VQ: Progressive Image Compression from Pretrained Vector Quantizerscited by 0