Denoising Textures is a Different Ballgame Altogether!

The paper investigates how current image denoisers handle textures, finding that generic denoising models often over‑smooth fine patterns and that improving texture performance requires fine‑tuning on texture‑specific datasets. However, such fine‑tuning causes the models to lose their ability to denoise the original data, indicating a trade‑off. The authors argue that dedicated, texture‑aware denoisers are necessary for accurate texture reconstruction and for downstream tasks like generative modeling.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

• fine-tuning
• benchmarks