4 papers
Informative Rays Selection for Few-Shot Neural Radiance Fields
Marco Orsingher, Anthony Dell'Eva, Paolo Zani +2
Neural Radiance Fields (NeRF) have recently emerged as a powerful method for image-based 3D reconstruction, but the lengthy per-scene optimization limits their practical usage, esp…
Learning Neural Radiance Fields from Multi-View Geometry
Marco Orsingher, Paolo Zani, Paolo Medici +1
We present a framework, called MVG-NeRF, that combines classical Multi-View Geometry algorithms and Neural Radiance Fields (NeRF) for image-based 3D reconstruction. NeRF has revolu…
Revisiting PatchMatch Multi-View Stereo for Urban 3D Reconstruction
Marco Orsingher, Paolo Zani, Paolo Medici +1
In this paper, a complete pipeline for image-based 3D reconstruction of urban scenarios is proposed, based on PatchMatch Multi-View Stereo (MVS). Input images are firstly fed into…
Efficient View Clustering and Selection for City-Scale 3D Reconstruction
Marco Orsingher, Paolo Zani, Paolo Medici +1
Image datasets have been steadily growing in size, harming the feasibility and efficiency of large-scale 3D reconstruction methods. In this paper, a novel approach for scaling Mult…