activity
20222024
most citedDeep Learning on Implicit Neural Representations of Shapes

8 citations · 12 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2024

Connecting NeRFs, Images, and Text

Francesco Ballerini, Pierluigi Zama Ramirez, Roberto Mirabella +2

Neural Radiance Fields (NeRFs) have emerged as a standard framework for representing 3D scenes and objects, introducing a novel data type for information exchange and storage. Conc…

cs.CV2024

Test Time Training for Industrial Anomaly Segmentation

Alex Costanzino, Pierluigi Zama Ramirez, Mirko Del Moro +4

Anomaly Detection and Segmentation (AD&S) is crucial for industrial quality control. While existing methods excel in generating anomaly scores for each pixel, practical application…

cs.CV2023

Looking at words and points with attention: a benchmark for text-to-shape coherence

Andrea Amaduzzi, Giuseppe Lisanti, Samuele Salti +1

While text-conditional 3D object generation and manipulation have seen rapid progress, the evaluation of coherence between generated 3D shapes and input textual descriptions lacks…

cs.CV2023

Depth self-supervision for single image novel view synthesis

Giovanni Minelli, Matteo Poggi, Samuele Salti

In this paper, we tackle the problem of generating a novel image from an arbitrary viewpoint given a single frame as input. While existing methods operating in this setup aim at pr…

cs.CV20233 cited

ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects

Marco Toschi, Riccardo De Matteo, Riccardo Spezialetti +3

In this paper, we focus on the problem of rendering novel views from a Neural Radiance Field (NeRF) under unobserved light conditions. To this end, we introduce a novel dataset, du…

cs.CV2023

Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation

Adriano Cardace, Pierluigi Zama Ramirez, Samuele Salti +1

3D semantic segmentation is a critical task in many real-world applications, such as autonomous driving, robotics, and mixed reality. However, the task is extremely challenging due…