Multi-View Guided Multi-View Stereo
Matteo Poggi,Andrea Conti,Stefano Mattoccia,Matteo Poggi,Andrea Conti,Stefano Mattoccia
This paper introduces a novel deep framework for dense 3D reconstruction from multiple image frames, leveraging a sparse set of depth measurements gathered jointly with image acquisition. Given a deep multi-view stereo network, our framework uses sparse depth hints to guide the neural network by modulating the plane-sweep cost volume built during the forward step, enabling us to infer constantly m...
