DCC 2021 Documents | SigPort

DCC 2021

DCC 2021Virtual Conference - The Data Compression Conference (DCC) is an international forum for current work on data compression and related applications. Both theoretical and experimental work are of interest. Visit DCC 2021 website.

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DZip: improved general-purpose lossless compression based on novel neural network modeling

Reducing Image Compression Artifacts for Deep Neural Networks

Intra Block Partition Structure Prediction via Convolutional Neural Network

Domain-Specific Language Abstractions for Compression

Backward Weighted Coding

Compact Representation of Spatial Hierarchies and Topological Relationships

Guided Blocks WOM codes

Approximate Hashing for Bioinformatics

Point AE-DCGAN: A deep learning model for 3D point cloud lossy geometry compression

Compression of point cloud geometry through a single projection

A Grammar Compressor for Collections of Reads with Applications to the Construction of the BWT

A Viewport-Adaptive Rate Control Approach for Omnidirectional Video Coding

Optimized Adaptive Loop Filter in Versatile Video Coding

COMPRESSING DEEP NETWORKS USING FISHER SCORE OF FEATURE MAPS

A Comparison of Classical and Deep Learning-based Techniques for Compressing Signals in a Union of Subspaces

End-to-end deep-learning-based image compression for machine tasks, a study

ndzip: A High-Throughput Parallel Lossless Compressor for Scientific Data

Flow-grounded Dynamic Texture Synthesis for Video Compression

Efficient algorithms for decode efficient prefix codes

Compact Polyominoes

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