16 citations · 26 across the 9 of their papers we have counts for
9 papers · 1 filter
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…
Semantic Image Synthesis via Class-Adaptive Cross-Attention
Tomaso Fontanini, Claudio Ferrari, Giuseppe Lisanti +2
In semantic image synthesis the state of the art is dominated by methods that use customized variants of the SPatially-Adaptive DE-normalization (SPADE) layers, which allow for goo…
Automatic Generation of Semantic Parts for Face Image Synthesis
Tomaso Fontanini, Claudio Ferrari, Massimo Bertozzi +1
Semantic image synthesis (SIS) refers to the problem of generating realistic imagery given a semantic segmentation mask that defines the spatial layout of object classes. Most of t…
Memory-augmented Online Video Anomaly Detection
Leonardo Rossi, Vittorio Bernuzzi, Tomaso Fontanini +2
The ability to understand the surrounding scene is of paramount importance for Autonomous Vehicles (AVs). This paper presents a system capable to work in an online fashion, giving…
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…
Arbitrary Point Cloud Upsampling with Spherical Mixture of Gaussians
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 in…
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…
Leveraging Local Domains for Image-to-Image Translation
Anthony Dell'Eva, Fabio Pizzati, Massimo Bertozzi +1
Image-to-image (i2i) networks struggle to capture local changes because they do not affect the global scene structure. For example, translating from highway scenes to offroad, i2i…