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Found 60 papers, 26 papers with code
Greek Sign Language Recognition for the SL-ReDu Learning Platform
There has been increasing interest lately in developing education tools for sign language (SL) learning that enable self-assessment and objective evaluation of learners’ SL productions, assisting both students and their instructors.
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation
The field of tropical algebra is closely linked with the domain of neural networks with piecewise linear activations, since their output can be described via tropical polynomials in the max-plus semiring.
Mushroom Segmentation and 3D Pose Estimation from Point Clouds using Fully Convolutional Geometric Features and Implicit Pose Encoding
We have validated the effectiveness of the proposed implicit-based approach for a synthetic test set, as well as provided qualitative results for a small set of real acquired point clouds with depth sensors.
3D Facial Expressions through Analysis-by-Neural-Synthesis
Instead, SMIRK replaces the differentiable rendering with a neural rendering module that, given the rendered predicted mesh geometry, and sparsely sampled pixels of the input image, generates a face image.
Neural Text to Articulate Talk: Deep Text to Audiovisual Speech Synthesis achieving both Auditory and Photo-realism
Our method, which we call NEUral Text to ARticulate Talk (NEUTART), is a talking face generator that uses a joint audiovisual feature space, as well as speech-informed 3D facial reconstructions and a lip-reading loss for visual supervision.
Pre-training Music Classification Models via Music Source Separation
In this paper, we study whether music source separation can be used as a pre-training strategy for music representation learning, targeted at music classification tasks.
Feather: An Elegant Solution to Effective DNN Sparsification
Neural Network pruning is an increasingly popular way for producing compact and efficient models, suitable for resource-limited environments, while preserving high performance.
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras
Matrix Factorization (MF) has found numerous applications in Machine Learning and Data Mining, including collaborative filtering recommendation systems, dimensionality reduction, data visualization, and community detection.
Photorealistic and Identity-Preserving Image-Based Emotion Manipulation with Latent Diffusion Models
In this paper, we investigate the emotion manipulation capabilities of diffusion models with "in-the-wild" images, a rather unexplored application area relative to the vast and rapidly growing literature for image-to-image translation tasks.
Revisiting Tropical Polynomial Division: Theory, Algorithms and Application to Neural Networks
Furthermore, we develop a relationship of tropical polynomial division with the computation of the convex hull of unions of convex polyhedra and use it to derive an exact algorithm for tropical polynomial division.
ViDaS Video Depth-aware Saliency Network
We introduce ViDaS, a two-stream, fully convolutional Video, Depth-Aware Saliency network to address the problem of attention modeling ``in-the-wild", via saliency prediction in videos.
OVeNet: Offset Vector Network for Semantic Segmentation
Motivated by this prior, we design a novel two-head network, named Offset Vector Network (OVeNet), which generates both standard semantic predictions and a dense 2D offset vector field indicating the offset from each pixel to the respective seed pixel, which is used to compute an alternative, seed-based semantic prediction.
Medical Face Masks and Emotion Recognition from the Body: Insights from a Deep Learning Perspective
In this paper, we conduct insightful studies about the effect of face occlusion on emotion recognition performance, and showcase the superiority of full body input over the plain masked face.
Multi-Source Contrastive Learning from Musical Audio
Contrastive learning constitutes an emerging branch of self-supervised learning that leverages large amounts of unlabeled data, by learning a latent space, where pairs of different views of the same sample are associated.
VP-SLAM: A Monocular Real-time Visual SLAM with Points, Lines and Vanishing Points
Traditional monocular Visual Simultaneous Localization and Mapping (vSLAM) systems can be divided into three categories: those that use features, those that rely on the image itself, and hybrid models.
3D Neural Sculpting (3DNS): Editing Neural Signed Distance Functions
In recent years, implicit surface representations through neural networks that encode the signed distance have gained popularity and have achieved state-of-the-art results in various tasks (e. g. shape representation, shape reconstruction, and learning shape priors).
Neural Sign Reenactor: Deep Photorealistic Sign Language Retargeting
In this paper, we introduce a neural rendering pipeline for transferring the facial expressions, head pose, and body movements of one person in a source video to another in a target video.
Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
The recent state of the art on monocular 3D face reconstruction from image data has made some impressive advancements, thanks to the advent of Deep Learning.
Enhancing Affective Representations of Music-Induced EEG through Multimodal Supervision and latent Domain Adaptation
The study of Music Cognition and neural responses to music has been invaluable in understanding human emotions.
Neural Emotion Director: Speech-preserving semantic control of facial expressions in "in-the-wild" videos
In this paper, we introduce a novel deep learning method for photo-realistic manipulation of the emotional state of actors in "in-the-wild" videos.
Tropical Geometrical Zonotope Reduction as Applied to Neural Network Compression.
Based on this result, we propose geometrical neural network compression methods that employ the K-means algorithm.
Trainable Learning Rate
Selecting an appropriate learning rate for efficiently training deep neural networks is a difficult process that can be affected by numerous parameters, such as the dataset, the model architecture or even the batch size.
An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wild
In this work we tackle the task of video-based audio-visual emotion recognition, within the premises of the 2nd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW2).
Exploring Temporal Context and Human Movement Dynamics for Online Action Detection in Videos
Nowadays, the interaction between humans and robots is constantly expanding, requiring more and more human motion recognition applications to operate in real time.
Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition
To evaluate the performance of our method under real-world conditions we perform extensive experiments on the AffectNet and Aff-Wild2 datasets.
Ranked #8 on
Facial Expression Recognition (FER)
on AffectNet
(Accuracy (7 emotion) metric)
Facial Expression Recognition
Facial Expression Recognition (FER)
Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild
In this work we tackle the task of video-based visual emotion recognition in the wild.
Ranked #3 on
Emotion Recognition in Context
on BoLD
HTMD-Net: A Hybrid Masking-Denoising Approach to Time-Domain Monaural Singing Voice Separation
The advent of deep learning has led to the prevalence of deep neural network architectures for monaural music source separation, with end-to-end approaches that operate directly on the waveform level increasingly receiving research attention.
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms
Sound Event Detection and Audio Classification tasks are traditionally addressed through time-frequency representations of audio signals such as spectrograms.
Grounding Consistency: Distilling Spatial Common Sense for Precise Visual Relationship Detection
Scene Graph Generators (SGGs) are models that, given an image, build a directed graph where each edge represents a predicted subject predicate object triplet.
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning
In our work, we utilize a Multi-task Learning scheme, training the model to perform decompositions of the target sequence with target units of different granularity, from fine to coarse.
Independent Sign Language Recognition with 3D Body, Hands, and Face Reconstruction
Independent Sign Language Recognition is a complex visual recognition problem that combines several challenging tasks of Computer Vision due to the necessity to exploit and fuse information from hand gestures, body features and facial expressions.
Advances in the training, pruning and enforcement of shape constraints of Morphological Neural Networks using Tropical Algebra
In this paper we study an emerging class of neural networks based on the morphological operators of dilation and erosion.
Sparse Approximate Solutions to Max-Plus Equations with Application to Multivariate Convex Regression
In this work, we study the problem of finding approximate, with minimum support set, solutions to matrix max-plus equations, which we call sparse approximate solutions.
Multiscale Fractal Analysis on EEG Signals for Music-Induced Emotion Recognition
Emotion Recognition from EEG signals has long been researched as it can assist numerous medical and rehabilitative applications.
Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss
We present our winning submission to the First International Workshop on Bodily Expressed Emotion Understanding (BEEU) challenge.
ChildBot: Multi-Robot Perception and Interaction with Children
In this paper we present an integrated robotic system capable of participating in and performing a wide range of educational and entertainment tasks, in collaboration with one or more children.
WSRNet: Joint Spotting and Recognition of Handwritten Words
The related joint loss leads to a boost in recognition performance, while the Seq2Seq branch is used to create efficient word representations.
Orientation Attentive Robotic Grasp Synthesis with Augmented Grasp Map Representation
Inherent morphological characteristics in objects may offer a wide range of plausible grasping orientations that obfuscates the visual learning of robotic grasping.
Weight Pruning via Adaptive Sparsity Loss
Pruning neural networks has regained interest in recent years as a means to compress state-of-the-art deep neural networks and enable their deployment on resource-constrained devices.
How to track your dragon: A Multi-Attentional Framework for real-time RGB-D 6-DOF Object Pose Tracking
We present a novel multi-attentional convolutional architecture to tackle the problem of real-time RGB-D 6D object pose tracking of single, known objects.
STAViS: Spatio-Temporal AudioVisual Saliency Network
We introduce STAViS, a spatio-temporal audiovisual saliency network that combines spatio-temporal visual and auditory information in order to efficiently address the problem of saliency estimation in videos.
Tropical Geometry and Piecewise-Linear Approximation of Curves and Surfaces on Weighted Lattices
Tropical Geometry and Mathematical Morphology share the same max-plus and min-plus semiring arithmetic and matrix algebra.
Tropical Polynomial Division and Neural Networks
In this work, we examine the process of Tropical Polynomial Division, a geometric method which seeks to emulate the division of regular polynomials, when applied to those of the max-plus semiring.
Augmentation Methods on Monophonic Audio for Instrument Classification in Polyphonic Music
Instrument classification is one of the fields in Music Information Retrieval (MIR) that has attracted a lot of research interest.
A linear method for camera pair self-calibration and multi-view reconstruction with geometrically verified correspondences
We introduce a linear method to self-calibrate and find the metric reconstruction of a camera pair.
RecNets: Channel-wise Recurrent Convolutional Neural Networks
In this paper, we introduce Channel-wise recurrent convolutional neural networks (RecNets), a family of novel, compact neural network architectures for computer vision tasks inspired by recurrent neural networks (RNNs).
Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship Detection
Detecting visual relationships, i. e. <Subject, Predicate, Object> triplets, is a challenging Scene Understanding task approached in the past via linguistic priors or spatial information in a single feature branch.
Fusing Body Posture with Facial Expressions for Joint Recognition of Affect in Child-Robot Interaction
In this paper we address the problem of multi-cue affect recognition in challenging scenarios such as child-robot interaction.
Detecting Adversarial Examples in Convolutional Neural Networks
This paper focuses on the detection of adversarial examples, which are created for convolutional neural networks that perform image classification.
SUSiNet: See, Understand and Summarize it
In this work we propose a multi-task spatio-temporal network, called SUSiNet, that can jointly tackle the spatio-temporal problems of saliency estimation, action recognition and video summarization.
Ranked #66 on
Action Recognition
on HMDB-51
(using extra training data)
LSTM-based Network for Human Gait Stability Prediction in an Intelligent Robotic Rollator
In this work, we present a novel framework for on-line human gait stability prediction of the elderly users of an intelligent robotic rollator using Long Short Term Memory (LSTM) networks, fusing multimodal RGB-D and Laser Range Finder (LRF) data from non-wearable sensors.
A Deep Learning Approach for Multi-View Engagement Estimation of Children in a Child-Robot Joint Attention task
In this work we tackle the problem of child engagement estimation while children freely interact with a robot in their room.
Tropical Modeling of Weighted Transducer Algorithms on Graphs
Weighted Finite State Transducers (WFSTs) are versatile data structures that can model a great number of problems, ranging from Automatic Speech Recognition to DNA sequencing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
An Adaptive Pruning Algorithm for Spoofing Localisation Based on Tropical Geometry
In particular, the proposed algorithm tries to localise the attacker by adapting the leniency parameter based on estimates about the state of the solution space.
A Tropical Approach to Neural Networks with Piecewise Linear Activations
We present a new, unifying approach following some recent developments on the complexity of neural networks with piecewise linear activations.
Multimodal Visual Concept Learning with Weakly Supervised Techniques
Despite the availability of a huge amount of video data accompanied by descriptive texts, it is not always easy to exploit the information contained in natural language in order to automatically recognize video concepts.
A Finite Element Computational Framework for Active Contours on Graphs
In this paper we present a new framework for the solution of active contour models on graphs.
Theoretical Analysis of Active Contours on Graphs
Active contour models based on partial differential equations have proved successful in image segmentation, yet the study of their geometric formulation on arbitrary geometric graphs is still at an early stage.
The DIRHA simulated corpus
This paper describes a multi-microphone multi-language acoustic corpus being developed under the EC project Distant-speech Interaction for Robust Home Applications (DIRHA).
Spectrum of Fractal Interpolation Functions
In this paper we compute the Fourier spectrum of the Fractal Interpolation Functions FIFs as introduced by Michael Barnsley.
Information Theory Information Theory
