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Efficient Variable Rate Image Compression With Multi-Scale Decomposition Network

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Deep Kalman Filtering Network for Video Compression Artifact Reduction
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Image compression with neural networks – A survey
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Quantization
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The JPEG still picture compression standard
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A theory for multiresolution signal decomposition: the wavelet representation
inferredcites →https://doi.org/10.1109/79.952802openalex-snapshot
Theoretical foundations of transform coding
inferredcites →https://doi.org/10.1109/83.136597openalex-snapshot
Image coding using wavelet transform
inferredcites →https://doi.org/10.1109/acssc.2003.1292216openalex-snapshot
Multiscale structural similarity for image quality assessment
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.577openalex-snapshot
Full Resolution Image Compression with Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00339openalex-snapshot
Learning Convolutional Networks for Content-Weighted Image Compression
inferredcites →https://doi.org/10.1109/cvpr.2018.00461openalex-snapshot
Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks
inferredcites →https://doi.org/10.1109/pcs.2016.7906310openalex-snapshot
End-to-end optimization of nonlinear transform codes for perceptual quality
inferredcites →https://doi.org/10.1109/proc.1972.8780openalex-snapshot
Transform picture coding
inferredcites →https://doi.org/10.1109/tcsvt.2012.2221191openalex-snapshot
Overview of the High Efficiency Video Coding (HEVC) Standard
inferredcites →https://doi.org/10.1109/tcsvt.2017.2734838openalex-snapshot
An End-to-End Compression Framework Based on Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tit.1981.1056282openalex-snapshot
Universal modeling and coding
inferredcites →https://doi.org/10.1117/1.1469618openalex-snapshot
Book Review: JPEG2000: Image Compression Fundamentals, Standards and Practice
inferredcites →https://doi.org/10.1162/neco_a_00505openalex-snapshot
What Is the Limit of Redundancy Reduction with Divisive Normalization?
inferredcites →https://doi.org/10.21236/ada164453openalex-snapshot
Learning Internal Representations by Error Propagation
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Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1506.05751openalex-snapshot
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1511.06281openalex-snapshot
Density Modeling of Images using a Generalized Normalization Transformation
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
inferredcites →https://doi.org/10.48550/arxiv.1611.01704openalex-snapshot
End-to-end Optimized Image Compression
inferredcites →https://doi.org/10.48550/arxiv.1704.00648openalex-snapshot
Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Exploring the Rate-Distortion-Complexity Optimization in Neural Image Compression
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Deep CSI Feedback for FDD MIMO Systems
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Image Compression Using Deep Convolutional Adversarial Networks
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Scalable Image Compression for Electric Power Inspection
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Optimized active contor segmentation model for medical image compression
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Learning-driven lossy image compression: A comprehensive survey
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Exploring the rate-distortion-complexity optimization in neural image compression
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A slimmable framework for practical neural video compression
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Deep Architectures for Image Compression: A Critical Review
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Vector quantization using k ‐means clustering neural network
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Review of compression approaches for optical remote-sensing images from post-processing perspective
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An image compression model via adaptive vector quantization: hybrid optimization algorithm
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Variable-Rate Deep Image Compression With Vision Transformers
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Slimmable Compressive Autoencoders for Practical Neural Image Compression
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ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training
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Rate Control for Learned Video Compression
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Survey On Image Compression Algorithms And Their Efficiencies Under Different Types Of Files
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Nonlinear Transform Coding
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SFTNet: Spatial-Frequency Transformer Network for Learned Image Compression
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Joint Degradation-Aware Arbitrary-Scale Super-Resolution for Variable-Rate Extreme Image Compression
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End-to-End Optimized Versatile Image Compression With Wavelet-Like Transform
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Remote Inference Over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector Quantization
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Learned Progressive Image Compression With Spatial Autoregression
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Deep Learning-Based Video Coding
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A Universal Optimization Framework for Learning-based Image Codec
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Remote Inference Over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector Quantization
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Learned Variable-Rate Image Compression with Residual Divisive Normalization
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