3 papers
cs.CV2026
Multiple Scale Latents for Learned Image Compression
Jonas Brenig, Radu Timofte
Most learned image compression systems rely on a single latent representation combined with a hyperprior, which limits their ability to efficiently capture image structure across s…
cs.CV2026
Mixture-of-Experts-based Entropy Model for Learned Image Compression
Jonas Brenig, Radu Timofte
Learned image compression has seen significant progress in recent years with the development of end-to-end learned models that achieve better compression efficiency than state-of-t…
eess.IV2025
Higher fidelity perceptual image and video compression with a latent conditioned residual denoising diffusion model
Jonas Brenig, Radu Timofte
Denoising diffusion models achieved impressive results on several image generation tasks often outperforming GAN based models. Recently, the generative capabilities of diffusion mo…