2 citations · 6 across the 17 of their papers we have counts for
23 papers
BoltNet: An Ultra-Lightweight Convolutional Network for On-Device Plant Species Identification
Daniel Rossi, Guido Borghi, Roberto Vezzani
Automated plant species identification from citizen-science imagery is an established, demanding fine-grained recognition problem: large taxonomic label spaces, visually similar sp…
SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses
Alessandro Simoni, Riccardo Catalini, Davide Di Nucci +6
Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in the literature. In particular,…
GazeD: Context-Aware Diffusion for Accurate 3D Gaze Estimation
Riccardo Catalini, Davide Di Nucci, Guido Borghi +5
We introduce GazeD, a new 3D gaze estimation method that jointly provides 3D gaze and human pose from a single RGB image. Leveraging the ability of diffusion models to deal with un…
RI-PIENO -- Revised and Improved Petrol-Filling Itinerary Estimation aNd Optimization
Marco Savarese, Antonio De Blasi, Carmine Zaccagnino +4
Efficient energy provisioning is a fundamental requirement for modern transportation systems, making refueling path optimization a critical challenge. Existing solutions often focu…
BRUM: Robust 3D Vehicle Reconstruction from 360 Sparse Images
Davide Di Nucci, Matteo Tomei, Guido Borghi +3
Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Field…
TakuNet: an Energy-Efficient CNN for Real-Time Inference on Embedded UAV systems in Emergency Response Scenarios
Daniel Rossi, Guido Borghi, Roberto Vezzani
Designing efficient neural networks for embedded devices is a critical challenge, particularly in applications requiring real-time performance, such as aerial imaging with drones a…
Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB
Alessandro Simoni, Francesco Marchetti, Guido Borghi +6
Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the…
KRONC: Keypoint-based Robust Camera Optimization for 3D Car Reconstruction
Davide Di Nucci, Alessandro Simoni, Matteo Tomei +3
The three-dimensional representation of objects or scenes starting from a set of images has been a widely discussed topic for years and has gained additional attention after the di…
3D Pose Nowcasting: Forecast the Future to Improve the Present
Alessandro Simoni, Francesco Marchetti, Guido Borghi +4
Technologies to enable safe and effective collaboration and coexistence between humans and robots have gained significant importance in the last few years. A critical component use…
CarPatch: A Synthetic Benchmark for Radiance Field Evaluation on Vehicle Components
Davide Di Nucci, Alessandro Simoni, Matteo Tomei +3
Neural Radiance Fields (NeRFs) have gained widespread recognition as a highly effective technique for representing 3D reconstructions of objects and scenes derived from sets of ima…
Semi-Perspective Decoupled Heatmaps for 3D Robot Pose Estimation from Depth Maps
Alessandro Simoni, Stefano Pini, Guido Borghi +1
Knowing the exact 3D location of workers and robots in a collaborative environment enables several real applications, such as the detection of unsafe situations or the study of mut…
Multi-Category Mesh Reconstruction From Image Collections
Alessandro Simoni, Stefano Pini, Roberto Vezzani +1
Recently, learning frameworks have shown the capability of inferring the accurate shape, pose, and texture of an object from a single RGB image. However, current methods are traine…
SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild
Ariel Caputo, Andrea Giachetti, Simone Soso +16
Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, ente…
Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face
Matteo Fabbri, Guido Borghi, Fabio Lanzi +3
Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face? Typically the answer is no. However, new deep architectures can generate RG…
Learn to See by Events: Color Frame Synthesis from Event and RGB Cameras
Stefano Pini, Guido Borghi, Roberto Vezzani
Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of…
Learning to Generate Facial Depth Maps
Stefano Pini, Filippo Grazioli, Guido Borghi +2
In this paper, an adversarial architecture for facial depth map estimation from monocular intensity images is presented. By following an image-to-image approach, we combine the adv…
Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World
Matteo Fabbri, Fabio Lanzi, Simone Calderara +3
Multi-People Tracking in an open-world setting requires a special effort in precise detection. Moreover, temporal continuity in the detection phase gains more importance when scene…
Face-from-Depth for Head Pose Estimation on Depth Images
Guido Borghi, Matteo Fabbri, Roberto Vezzani +2
Depth cameras allow to set up reliable solutions for people monitoring and behavior understanding, especially when unstable or poor illumination conditions make unusable common RGB…
Head Detection with Depth Images in the Wild
Diego Ballotta, Guido Borghi, Roberto Vezzani +1
Head detection and localization is a demanding task and a key element for many computer vision applications, like video surveillance, Human Computer Interaction and face analysis.…
From Depth Data to Head Pose Estimation: a Siamese approach
Marco Venturelli, Guido Borghi, Roberto Vezzani +1
The correct estimation of the head pose is a problem of the great importance for many applications. For instance, it is an enabling technology in automotive for driver attention mo…
Fast Gesture Recognition with Multiple Stream Discrete HMMs on 3D Skeletons
Guido Borghi, Roberto Vezzani, Rita Cucchiara
HMMs are widely used in action and gesture recognition due to their implementation simplicity, low computational requirement, scalability and high parallelism. They have worth perf…
Deep Head Pose Estimation from Depth Data for In-car Automotive Applications
Marco Venturelli, Guido Borghi, Roberto Vezzani +1
Recently, deep learning approaches have achieved promising results in various fields of computer vision. In this paper, we tackle the problem of head pose estimation through a Conv…
POSEidon: Face-from-Depth for Driver Pose Estimation
Guido Borghi, Marco Venturelli, Roberto Vezzani +1
Fast and accurate upper-body and head pose estimation is a key task for automatic monitoring of driver attention, a challenging context characterized by severe illumination changes…