DynIBaR: Neural Dynamic Image-Based Rendering

HyperNeRF NSFF Ours HyperNeRF NSFF Ours GT 0.31 0.19 0.04 Figure 1. Recent methods for synthesizing novel views from monocular videos of dynamic scenes-like HyperNeRF [50] and NSFF [35] struggle to render high-quality views from long videos featuring complex camera and scene motion. We present a new approach that addresses these limitations, illustrated above via an application to 6DoF video stabilization, where we apply our approach and prior methods on a 30-second, shaky video clip, and compare novel views rendered along a smoothed camera path (left). On a dynamic scenes dataset (right) [75], our approach significantly improves rendering fidelity, as indicated by synthesized images and LPIPS errors computed on pixels corresponding to moving objects (yellow numbers). Please see the supplementary video for full results.