Search Results for author: Marco Orsingher

Found 5 papers, 1 papers with code

Informative Rays Selection for Few-Shot Neural Radiance Fields

no code implementations29 Dec 2023 Marco Orsingher, Anthony Dell'Eva, Paolo Zani, Paolo Medici, Massimo Bertozzi

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, especially in resource-constrained settings.

3D Reconstruction Diversity

Learning Neural Radiance Fields from Multi-View Geometry

no code implementations24 Oct 2022 Marco Orsingher, Paolo Zani, Paolo Medici, Massimo Bertozzi

We present a framework, called MVG-NeRF, that combines classical Multi-View Geometry algorithms and Neural Radiance Fields (NeRF) for image-based 3D reconstruction.

3D Reconstruction Novel View Synthesis

Arbitrary Point Cloud Upsampling with Spherical Mixture of Gaussians

1 code implementation10 Aug 2022 Anthony Dell'Eva, Marco Orsingher, Massimo Bertozzi

Generating dense point clouds from sparse raw data benefits downstream 3D understanding tasks, but existing models are limited to a fixed upsampling ratio or to a short range of integer values.

Decoder point cloud upsampling

Revisiting PatchMatch Multi-View Stereo for Urban 3D Reconstruction

no code implementations18 Jul 2022 Marco Orsingher, Paolo Zani, Paolo Medici, Massimo Bertozzi

In this paper, a complete pipeline for image-based 3D reconstruction of urban scenarios is proposed, based on PatchMatch Multi-View Stereo (MVS).

3D Reconstruction

Efficient View Clustering and Selection for City-Scale 3D Reconstruction

no code implementations18 Jul 2022 Marco Orsingher, Paolo Zani, Paolo Medici, Massimo Bertozzi

Image datasets have been steadily growing in size, harming the feasibility and efficiency of large-scale 3D reconstruction methods.

3D Reconstruction Clustering

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