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Neural video compression with feature modulation
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 …
commonly-used residual coding-based codec and the latest NVC already claims to …
Generative visual compression: A review
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 …
acquisition of digital content and impelling the progress of visual compression towards …
High-fidelity image compression with score-based generative models
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 …
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
Traditional image codecs prioritize signal fidelity and human perception, often neglecting
machine vision tasks. Deep learning approaches have shown promising coding …
machine vision tasks. Deep learning approaches have shown promising coding …
Consistency Guided Diffusion Model with Neural Syntax for Perceptual Image Compression
Diffusion models show impressive performances in image generation with excellent
perceptual quality. However, its tendency to introduce additional distortion prevents its direct …
perceptual quality. However, its tendency to introduce additional distortion prevents its direct …
Bridging the Gap between Diffusion Models and Universal Quantization for Image Compression
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 …
image compression codecs can be built by using a diffusion model to “denoise” the artifacts …