[Compression] Learned Image Compression 유형별 최근 논문 정리

es.Seong·2024년 5월 29일
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VAE + Hyperprior + Context Module based (ELIC,2022 ~)

PO-ELIC: Perception-Oriented Efficient Learned Image Coding (CVPR, 2022)

SegPIC: Region-Adaptive Transform with Segmentation Prior for Image Compression (2024)

MLIC: Multi-Reference Entropy Model for Learned Image Compression (ACMMM, 2022)

MLIC++: Linear Complexity Multi-Reference Entropy Modeling for Learned Image Compression (ICML, 2023)


Transformer Based

Entroformer: A Transformer-based Entropy Model for Learned Image Compression (ICLR, 2022)

Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression (ECCV, 2022)

LIC-TCM: Learned Image Compression with Mixed Transformer-CNN Architectures (CVPR, 2023)

STF, WACNN: The Devil Is in the Details: Window-based Attention for Image Compression (CVPR, 2022)


GAN

HIFIC: High-Fidelity Generative Image Compression (NeurIPS 2020)​


Diffusion

CDC: Lossy Image Compression with Conditional Diffusion Models (NeurIPS , 2022)


Implicit Neural Representation

COIN: COmpression with Implicit Neural representations (ICLR, 2021)

COIN++: Neural Compression Across Modalities (TMLR, 2022)

RQAT-INR: Improved Implicit Neural Image Compression (Data Compression Conference, 2023)

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Graduate student at Pusan National University, majoring in Artificial Intelligence

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