Preprint
Aug 2026
When Latents Forget Pixels: Restoring Fidelity in Diffusion Transformer Super-Resolution
This work proposes a pixel-grounded super-resolution (PGSR) framework that preserves LR-observed pixel evidence before VAE compression and reuses it throughout restoration and improves the realism--fidelity trade-off and produces more faithful, visually convincing results than existing latent generative SR approaches.
Yuehao Shi, Yuyao Zhang, Yu-Wing Tai
· 0 citations