arXiv:2401.02156
공식 코드 · Papers with Code
Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder
원문 초록
This paper summarises the design of the Cool-Chic candidate for the Challenge on Learned Image Compression. This candidate attempts to demonstrate that neural coding methods can lead to low complexity and lightweight image decoders while still offering competitive performance. The approach is based on the already published overfitted lightweight neural networks Cool-Chic, further adapted to the human subjective viewing targeted in this challenge.
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Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic Inference
NIC-RobustBench: A Comprehensive Open-Source Toolkit for Neural Image Compression and Robustness Analysis
DiffO: Single-step Diffusion for Image Compression at Ultra-Low Bitrates
ABC: Adaptive BayesNet Structure Learning for Computational Scalable Multi-task Image Compression
Flexible Mixed Precision Quantization for Learned Image Compression
Structured Pruning and Quantization for Learned Image Compression
토론
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