Super-resolution Techniques for Enhancing NeRF-generated Images
Summary:
- Super-resolution (SR) techniques have been used to improve the quality of images generated by neural radiance fields (NeRF).
- Existing methods for combining NeRF and SR often require additional input features, loss functions, or expensive training procedures.
- This paper proposes a simple NeRF+SR pipeline that directly combines existing modules, aiming to achieve efficiency gains without costly training or architectural changes.
- The researchers also introduce a lightweight augmentation technique to improve the quality of NeRF+SR generated images.
Author’s take:
This paper presents a straightforward approach to integrating super-resolution techniques with neural radiance fields, aimed at enhancing the efficiency of the process. By avoiding additional complexities and expensive training procedures, this approach offers a lightweight solution for generating high-quality images. The introduction of a lightweight augmentation technique further improves the quality of the images produced. Ultimately, this research contributes to the advancement of super-resolution techniques in the context of neural radiance fields.