Neural video compression with feature modulation

J Li, B Li, Y Lu - Proceedings of the IEEE/CVF Conference …, 2024 - openaccess.thecvf.com
The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …

Generative visual compression: A review

B Chen, S Yin, P Chen, S Wang… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Artificial Intelligence Generated Content (AIGC) is leading a new technical revolution for the
acquisition of digital content and impelling the progress of visual compression towards …

High-fidelity image compression with score-based generative models

E Hoogeboom, E Agustsson, F Mentzer… - arxiv preprint arxiv …, 2023 - arxiv.org
Despite the tremendous success of diffusion generative models in text-to-image generation,
replicating this success in the domain of image compression has proven difficult. In this …

Toward scalable image feature compression: a content-adaptive and diffusion-based approach

S Guo, Z Chen, Y Zhao, N Zhang, X Li… - Proceedings of the 31st …, 2023 - dl.acm.org
Traditional image codecs prioritize signal fidelity and human perception, often neglecting
machine vision tasks. Deep learning approaches have shown promising coding …

Consistency Guided Diffusion Model with Neural Syntax for Perceptual Image Compression

H Kuang, Y Ma, W Yang, Z Guo, J Liu - Proceedings of the 32nd ACM …, 2024 - dl.acm.org
Diffusion models show impressive performances in image generation with excellent
perceptual quality. However, its tendency to introduce additional distortion prevents its direct …

Bridging the Gap between Diffusion Models and Universal Quantization for Image Compression

L Relic, R Azevedo, Y Zhang… - Machine Learning …, 2024 - research-collection.ethz.ch
By leveraging the similarities between quantization error and additive noise, diffusion-based
image compression codecs can be built by using a diffusion model to “denoise” the artifacts …