UP-NeRF: Unconstrained Pose Prior-Free Neural Radiance Field

Neural Radiance Field (NeRF) has enabled novel view synthesis with high fidelity given images and camera poses. Subsequent works even succeeded in eliminating the necessity of pose priors by jointly optimizing NeRF and camera pose. However, these works are limited to relatively simple settings such as photometrically consistent and occluder-free image collections or a sequence of images from a video. So they have difficulty handling unconstrained images with varying illumination and transient occluders. In this paper, we propose UP-NeRF (Unconstrained Pose-prior-free Neural Radiance Fields) to optimize NeRF with unconstrained image collections without camera pose prior.