CVPR2023

We propose a neural lens model that is versatile, easy to use and can be trivially used in gradient-based optimization pipelines for point projection and rendering. We also propose a new dataset for evaluation of lens and calibration models and a new strategy to create marker boards for calibration.

We create a drivable and accurate hair representation using neural rendering primitives and temporal models.