27 citations · 36 across the 17 of their papers we have counts for
19 papers
Polyglot: Multilingual Style Preserving Speech-Driven Facial Animation
Federico Nocentini, Kwanggyoon Seo, Qingju Liu +6
Speech-Driven Facial Animation (SDFA) has gained significant attention due to its applications in movies, video games, and virtual reality. However, most existing models are traine…
FreeTalk: Emotional Topology-Free 3D Talking Heads
Federico Nocentini, Thomas Besnier, Claudio Ferrari +2
Speech-driven 3D facial animation has advanced rapidly, yet most approaches remain tied to registered template meshes, preventing effective deployment on raw 3D scans with arbitrar…
Revisiting Emotions Representation for Recognition in the Wild
Joao Baptista Cardia Neto, Claudio Ferrari, Stefano Berretti
Facial emotion recognition has been typically cast as a single-label classification problem of one out of six prototypical emotions. However, that is an oversimplification that is…
3D Face Reconstruction Error Decomposed: A Modular Benchmark for Fair and Fast Method Evaluation
Evangelos Sariyanidi, Claudio Ferrari, Federico Nocentini +3
Computing the standard benchmark metric for 3D face reconstruction, namely geometric error, requires a number of steps, such as mesh cropping, rigid alignment, or point corresponde…
Spatio-temporal Transformers for Action Unit Classification with Event Cameras
Luca Cultrera, Federico Becattini, Lorenzo Berlincioni +2
Face analysis has been studied from different angles to infer emotion, poses, shapes, and landmarks. Traditionally RGB cameras are used, yet for fine-grained tasks standard sensors…
Beyond Fixed Topologies: Unregistered Training and Comprehensive Evaluation Metrics for 3D Talking Heads
Federico Nocentini, Thomas Besnier, Claudio Ferrari +3
Generating speech-driven 3D talking heads presents numerous challenges; among those is dealing with varying mesh topologies where no point-wise correspondence exists across the mes…
Neuromorphic Facial Analysis with Cross-Modal Supervision
Federico Becattini, Luca Cultrera, Lorenzo Berlincioni +3
Traditional approaches for analyzing RGB frames are capable of providing a fine-grained understanding of a face from different angles by inferring emotions, poses, shapes, landmark…
EmoVOCA: Speech-Driven Emotional 3D Talking Heads
Federico Nocentini, Claudio Ferrari, Stefano Berretti
The domain of 3D talking head generation has witnessed significant progress in recent years. A notable challenge in this field consists in blending speech-related motions with expr…
ScanTalk: 3D Talking Heads from Unregistered Scans
Federico Nocentini, Thomas Besnier, Claudio Ferrari +3
Speech-driven 3D talking heads generation has emerged as a significant area of interest among researchers, presenting numerous challenges. Existing methods are constrained by anima…
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…
Learning Landmarks Motion from Speech for Speaker-Agnostic 3D Talking Heads Generation
Federico Nocentini, Claudio Ferrari, Stefano Berretti
This paper presents a novel approach for generating 3D talking heads from raw audio inputs. Our method grounds on the idea that speech related movements can be comprehensively and…
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…
The Florence 4D Facial Expression Dataset
F. Principi, S. Berretti, C. Ferrari +3
Human facial expressions change dynamically, so their recognition / analysis should be conducted by accounting for the temporal evolution of face deformations either in 2D or 3D. W…
Generating Multiple 4D Expression Transitions by Learning Face Landmark Trajectories
Naima Otberdout, Claudio Ferrari, Mohamed Daoudi +2
In this work, we address the problem of 4D facial expressions generation. This is usually addressed by animating a neutral 3D face to reach an expression peak, and then get back to…
What makes you, you? Analyzing Recognition by Swapping Face Parts
Claudio Ferrari, Matteo Serpentoni, Stefano Berretti +1
Deep learning advanced face recognition to an unprecedented accuracy. However, understanding how local parts of the face affect the overall recognition performance is still mostly…
Sparse to Dense Dynamic 3D Facial Expression Generation
Naima Otberdout, Claudio Ferrari, Mohamed Daoudi +2
In this paper, we propose a solution to the task of generating dynamic 3D facial expressions from a neutral 3D face and an expression label. This involves solving two sub-problems:…
Inner Eye Canthus Localization for Human Body Temperature Screening
Claudio Ferrari, Lorenzo Berlincioni, Marco Bertini +1
In this paper, we propose an automatic approach for localizing the inner eye canthus in thermal face images. We first coarsely detect 5 facial keypoints corresponding to the center…
A Sparse and Locally Coherent Morphable Face Model for Dense Semantic Correspondence Across Heterogeneous 3D Faces
Claudio Ferrari, Stefano Berretti, Pietro Pala +1
The 3D Morphable Model (3DMM) is a powerful statistical tool for representing 3D face shapes. To build a 3DMM, a training set of face scans in full point-to-point correspondence is…
Additional Baseline Metrics for the paper "Extended YouTube Faces: a Dataset for Heterogeneous Open-Set Face Identification"
Claudio Ferrari, Stefano Berretti, Alberto Del Bimbo
In this report, we provide additional and corrected results for the paper "Extended YouTube Faces: a Dataset for Heterogeneous Open-Set Face Identification". After further investig…