Zhuoran Zheng

Loop-Mamba not only restores old photos more effectively but also introduces a novel degradation-aware framework that outperforms state-of-the-art methods by leveraging persistent memory and semantic guidance.

By combining VLM-guided segmentation with spectral analysis, this approach offers a more interpretable and accurate alternative to traditional classifiers for veterinary diagnosis, sidestepping reliance on large labeled datasets.

Ditch pixel-by-pixel processing: C$^2$SSM achieves state-of-the-art UHD image restoration by scanning semantic clusters, not individual pixels, for a massive efficiency boost.