Flow Supervised Neural Radiance Fields for Static-Dynamic Decomposition
Quei-An Chen,Akihiro Tsukada,Quei-An Chen,Akihiro Tsukada
We present an approach to synthesize novel views from dynamics scenes captured by multi-view videos of cameras mounted on a driving vehicle. We unify existing methods and propose a new training loss to explicitly disentangle the static background from the dynamic foreground objects using scene flow's magnitude, learnt only from proxy 2D optical flow supervision. We obtain high quality static and d...
