outperforms existing generative image compression approaches across
a range of metrics, including perceptual distortion, statistical fidelity, and
no-reference quality assessments.</p>
            
            <p class="paper-tldr"><strong>TLDR</strong>: This paper introduces a novel diffusion-based generative image compression framework that directly reverses the compression process using stochastic differential equations (SDEs), achieving realistic reconstructions with efficient rate adjustment.</p>
     