2 citations · 3 across the 6 of their papers we have counts for
7 papers
VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes
Giulia Martinelli, Niccolò Bisagno, Nicola Garau +2
We introduce VolHuMe, a dataset of high-quality 4D human scans captured with a state-of-the-art volumetric studio using 64 RGB and 32 depth cameras. VolHuMe contains individual cap…
SDFoam: Signed-Distance Foam for explicit surface reconstruction
Antonella Rech, Nicola Conci, Nicola Garau
Neural radiance fields (NeRF) have driven impressive progress in view synthesis by using ray-traced volumetric rendering. Splatting-based methods such as 3D Gaussian Splatting (3DG…
EPOCH: Jointly Estimating the 3D Pose of Cameras and Humans
Nicola Garau, Giulia Martinelli, Niccolò Bisagno +2
Monocular Human Pose Estimation (HPE) aims at determining the 3D positions of human joints from a single 2D image captured by a camera. However, a single 2D point in the image may…
A Unified Simulation Framework for Visual and Behavioral Fidelity in Crowd Analysis
Niccolò Bisagno, Nicola Garau, Antonio Luigi Stefani +1
Simulation is a powerful tool to easily generate annotated data, and a highly desirable feature, especially in those domains where learning models need large training datasets. Mac…
Capsules as viewpoint learners for human pose estimation
Nicola Garau, Nicola Conci
The task of human pose estimation (HPE) deals with the ill-posed problem of estimating the 3D position of human joints directly from images and videos. In recent literature, most o…
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks
Nicola Garau, Niccolò Bisagno, Zeno Sambugaro +1
Deep neural networks achieve outstanding results in a large variety of tasks, often outperforming human experts. However, a known limitation of current neural architectures is the…
DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders
Nicola Garau, Niccolò Bisagno, Piotr Bródka +1
Human Pose Estimation (HPE) aims at retrieving the 3D position of human joints from images or videos. We show that current 3D HPE methods suffer a lack of viewpoint equivariance, n…