Translated data: Researchers from the University of Maryland and Meta AI have jointly proposed a new video matting method called OmnimatteRF, which utilizes both 2D foreground layers and 3D background models for video separation. The method initially employs traditional masking techniques to isolate the foreground layer, then trains a TensoRF model to represent the background, and finally combines the foreground and background to reconstruct the scene. The researchers have validated this technology on multiple datasets, demonstrating improved reconstruction effects. It can be applied in post-production of videos and also aids in the creation of immersive virtual environments.