no code implementations • ECCV 2020 • Ioannis Marras, Grigorios G. Chrysos, Ioannis Alexiou, Gregory Slabaugh, Stefanos Zafeiriou
Deep Convolutional Neural Networks (CNNs) have been successfully used in many low-level vision problems like image denoising.
2 code implementations • ECCV 2020 • Jiankang Deng, Jia Guo, Tongliang Liu, Mingming Gong, Stefanos Zafeiriou
In this paper, we relax the intra-class constraint of ArcFace to improve the robustness to label noise.
no code implementations • ECCV 2020 • Haoyang Wang, Riza Alp Güler, Iasonas Kokkinos, George Papandreou, Stefanos Zafeiriou
We introduce BLSM, a bone-level skinned model of the human body mesh where bone scales are set prior to template synthesis, rather than the common, inverse practice.
no code implementations • 9 Jan 2025 • Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias, Alexandros Lattas, Stefanos Zafeiriou
Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, we introduce Arc2Avatar, the first SDS-based method utilizing a human face foundation model as guidance with just a single image as input.
no code implementations • 17 Dec 2024 • Zhengdi Yu, Stefanos Zafeiriou, Tolga Birdal
We propose Dyn-HaMR, to the best of our knowledge, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild.
no code implementations • 26 Nov 2024 • Ronglai Zuo, Rolandos Alexandros Potamias, Evangelos Ververas, Jiankang Deng, Stefanos Zafeiriou
Most existing approaches treat SLG as a visual content generation task, employing techniques such as diffusion models to produce sign videos, 2D keypoints, or 3D avatars based on text inputs, overlooking the linguistic properties of sign languages.
1 code implementation • 18 Sep 2024 • Rolandos Alexandros Potamias, Jinglei Zhang, Jiankang Deng, Stefanos Zafeiriou
In recent years, 3D hand pose estimation methods have garnered significant attention due to their extensive applications in human-computer interaction, virtual reality, and robotics.
Ranked #1 on
3D Hand Pose Estimation
on HO-3D v2
1 code implementation • 29 Aug 2024 • Simone Foti, Stefanos Zafeiriou, Tolga Birdal
Seams, distortions, wasted UV space, vertex-duplication, and varying resolution over the surface are the most prominent issues of the standard UV-based texturing of meshes.
no code implementations • 4 Jul 2024 • Dimitrios Kollias, Stefanos Zafeiriou, Irene Kotsia, Abhinav Dhall, Shreya Ghosh, Chunchang Shao, Guanyu Hu
s-Aff-Wild2, which is a static version of the A/V Aff-Wild2 database and contains annotations for valence-arousal, expressions and Action Units, is utilized for the purposes of the Multi-Task Learning Challenge; a part of C-EXPR-DB, which is an A/V in-the-wild database with compound expression annotations, is utilized for the purposes of the Compound Expression Recognition Challenge.
no code implementations • 26 May 2024 • Francesca Babiloni, Alexandros Lattas, Jiankang Deng, Stefanos Zafeiriou
We propose ID-to-3D, a method to generate identity- and text-guided 3D human heads with disentangled expressions, starting from even a single casually captured in-the-wild image of a subject.
no code implementations • 17 May 2024 • Michail Tarasiou, Stylianos Moschoglou, Jiankang Deng, Stefanos Zafeiriou
We then use these synthetic captions to fine-tune a text-to-image diffusion model.
no code implementations • 29 Apr 2024 • Evangelos Ververas, Rolandos Alexandros Potamias, Jifei Song, Jiankang Deng, Stefanos Zafeiriou
In this work, we propose a structure-aware Gaussian Splatting method (SAGS) that implicitly encodes the geometry of the scene, which reflects to state-of-the-art rendering performance and reduced storage requirements on benchmark novel-view synthesis datasets.
no code implementations • CVPR 2024 • Jiali Zheng, Rolandos Alexandros Potamias, Stefanos Zafeiriou
In recent years, there has been a significant shift in the field of digital avatar research, towards modeling, animating and reconstructing clothed human representations, as a key step towards creating realistic avatars.
no code implementations • 28 Mar 2024 • Rolandos Alexandros Potamias, Michail Tarasiou, Stylianos Ploumpis, Stefanos Zafeiriou
In the realm of 3D computer vision, parametric models have emerged as a ground-breaking methodology for the creation of realistic and expressive 3D avatars.
no code implementations • 25 Mar 2024 • Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias, Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis, Stefanos Zafeiriou
Recent advances in diffusion models have notably enhanced the capabilities of generative models in 2D animation.
2 code implementations • 18 Mar 2024 • Foivos Paraperas Papantoniou, Alexandros Lattas, Stylianos Moschoglou, Jiankang Deng, Bernhard Kainz, Stefanos Zafeiriou
This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models.
Ranked #1 on
Diffusion Personalization Tuning Free
on AgeDB
no code implementations • 29 Feb 2024 • Dimitrios Kollias, Panagiotis Tzirakis, Alan Cowen, Stefanos Zafeiriou, Irene Kotsia, Alice Baird, Chris Gagne, Chunchang Shao, Guanyu Hu
This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024.
2 code implementations • ICCV 2023 • Guanxiong Sun, Chi Wang, Zhaoyu Zhang, Jiankang Deng, Stefanos Zafeiriou, Yang Hua
Then, these video prompts are prepended to the patch embeddings of the current frame as the updated input for video feature extraction.
1 code implementation • CVPR 2024 • Michail Tarasiou, Rolandos Alexandros Potamias, Eimear O'Sullivan, Stylianos Ploumpis, Stefanos Zafeiriou
We present the Locally Adaptive Morphable Model (LAMM), a highly flexible Auto-Encoder (AE) framework for learning to generate and manipulate 3D meshes.
no code implementations • 2 Jan 2024 • Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Multi-Task Learning (MTL) is a framework, where multiple related tasks are learned jointly and benefit from a shared representation space, or parameter transfer.
Ranked #3 on
Facial Expression Recognition (FER)
on RAF-DB
(Avg. Accuracy metric, using extra
training data)
no code implementations • 7 Dec 2023 • Stathis Galanakis, Alexandros Lattas, Stylianos Moschoglou, Stefanos Zafeiriou
The remarkable progress in 3D face reconstruction has resulted in high-detail and photorealistic facial representations.
no code implementations • CVPR 2024 • Vasileios Baltatzis, Rolandos Alexandros Potamias, Evangelos Ververas, Guanxiong Sun, Jiankang Deng, Stefanos Zafeiriou
Sign Languages (SL) serve as the primary mode of communication for the Deaf and Hard of Hearing communities.
2 code implementations • 1 Dec 2023 • Michail Tarasiou, Jiankang Deng, Stefanos Zafeiriou
Heterogeneous face recognition (HFR) involves the intricate task of matching face images across the visual domains of visible (VIS) and near-infrared (NIR).
no code implementations • 29 Nov 2023 • Stylianos Bakas, Siegfried Ludwig, Dimitrios A. Adamos, Nikolaos Laskaris, Yannis Panagakis, Stefanos Zafeiriou
We delineate a trade-off relationship between increased classification accuracy when alignment is performed at later modeling stages, and susceptibility to class-imbalance in the set of trials that the statistics are computed on.
no code implementations • 6 Oct 2023 • Jiali Zheng, Youngkyoon Jang, Athanasios Papaioannou, Christos Kampouris, Rolandos Alexandros Potamias, Foivos Paraperas Papantoniou, Efstathios Galanakis, Ales Leonardis, Stefanos Zafeiriou
This paper introduces the Imperial Light-Stage Head (ILSH) dataset, a novel light-stage-captured human head dataset designed to support view synthesis academic challenges for human heads.
no code implementations • CVPR 2023 • Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis, Baris Gecer, Jiankang Deng, Stefanos Zafeiriou
In this paper, we introduce FitMe, a facial reflectance model and a differentiable rendering optimization pipeline, that can be used to acquire high-fidelity renderable human avatars from single or multiple images.
no code implementations • ICCV 2023 • Foivos Paraperas Papantoniou, Alexandros Lattas, Stylianos Moschoglou, Stefanos Zafeiriou
Following the remarkable success of diffusion models on image generation, recent works have also demonstrated their impressive ability to address a number of inverse problems in an unsupervised way, by properly constraining the sampling process based on a conditioning input.
no code implementations • 2 Mar 2023 • Dimitrios Kollias, Panagiotis Tzirakis, Alice Baird, Alan Cowen, Stefanos Zafeiriou
The fifth Affective Behavior Analysis in-the-wild (ABAW) Competition is part of the respective ABAW Workshop which will be held in conjunction with IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2023.
3 code implementations • CVPR 2023 • Michail Tarasiou, Erik Chavez, Stefanos Zafeiriou
In this paper we introduce the Temporo-Spatial Vision Transformer (TSViT), a fully-attentional model for general Satellite Image Time Series (SITS) processing based on the Vision Transformer (ViT).
1 code implementation • CVPR 2023 • Rolandos Alexandros Potamias, Stylianos Ploumpis, Stylianos Moschoglou, Vasileios Triantafyllou, Stefanos Zafeiriou
Currently, most of the state-of-the-art reconstruction and pose estimation methods rely on the low polygon MANO model.
1 code implementation • ICCV 2023 • Francesca Babiloni, Matteo Maggioni, Thomas Tanay, Jiankang Deng, Ales Leonardis, Stefanos Zafeiriou
The success of deep learning models on structured data has generated significant interest in extending their application to non-Euclidean domains.
3 code implementations • 6 Dec 2022 • Evangelos Ververas, Polydefkis Gkagkos, Jiankang Deng, Michail Christos Doukas, Jia Guo, Stefanos Zafeiriou
To close the gap between image domains, we create a large-scale dataset of diverse faces with gaze pseudo-annotations, which we extract based on the 3D geometry of the scene, and design a multi-view supervision framework to balance their effect during training.
no code implementations • 25 Nov 2022 • Michail Christos Doukas, Stylianos Ploumpis, Stefanos Zafeiriou
We present Dynamic Neural Portraits, a novel approach to the problem of full-head reenactment.
1 code implementation • 11 Nov 2022 • Yunqi Miao, Alexandros Lattas, Jiankang Deng, Jungong Han, Stefanos Zafeiriou
Specifically, we reconstruct 3D face shape and reflectance from a large 2D facial dataset and introduce a novel method of transforming the VIS reflectance to NIR reflectance.
1 code implementation • 5 Nov 2022 • Tao Wang, Kaihao Zhang, Xuanxi Chen, Wenhan Luo, Jiankang Deng, Tong Lu, Xiaochun Cao, Wei Liu, Hongdong Li, Stefanos Zafeiriou
Second, we discuss the challenges of face restoration.
no code implementations • 15 Sep 2022 • Stathis Galanakis, Baris Gecer, Alexandros Lattas, Stefanos Zafeiriou
In this work, we present a facial 3D Morphable Model, which exploits both of the above, and can accurately model a subject's identity, pose and expression and render it in arbitrary illumination.
1 code implementation • 11 Sep 2022 • Konstantinos Panagiotis Alexandridis, Shan Luo, Anh Nguyen, Jiankang Deng, Stefanos Zafeiriou
The long-tailed distribution is a common phenomenon in the real world.
1 code implementation • 4 Aug 2022 • Zhipeng Du, Miaojing Shi, Jiankang Deng, Stefanos Zafeiriou
In this work, we redesign the multi-scale neural network by introducing a hierarchical mixture of density experts, which hierarchically merges multi-scale density maps for crowd counting.
no code implementations • 3 Aug 2022 • Michail Christos Doukas, Evangelos Ververas, Viktoriia Sharmanska, Stefanos Zafeiriou
We present Free-HeadGAN, a person-generic neural talking head synthesis system.
no code implementations • 30 May 2022 • Rolandos Alexandros Potamias, Alexandros Neofytou, Kyriaki-Margarita Bintsi, Stefanos Zafeiriou
To address such limitations and alleviate the computational burden, we propose a learnable network to approximate geodesic paths.
1 code implementation • CVPR 2022 • Qingping Zheng, Jiankang Deng, Zheng Zhu, Ying Li, Stefanos Zafeiriou
Specifically, DML-CSR designs a multi-task model which comprises face parsing, binary edge, and category edge detection.
Ranked #1 on
Face Parsing
on Helen
1 code implementation • 18 Mar 2022 • Xingyu Ren, Alexandros Lattas, Baris Gecer, Jiankang Deng, Chao Ma, Xiaokang Yang, Stefanos Zafeiriou
Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed.
1 code implementation • 11 Mar 2022 • Michail Tarasiou, Stefanos Zafeiriou
In training machine learning models for land cover semantic segmentation there is a stark contrast between the availability of satellite imagery to be used as inputs and ground truth data to enable supervised learning.
1 code implementation • 14 Feb 2022 • Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup, Alexandre Gramfort, Sylvain Chevallier, Vinay Jayaram, Camille Jeunet, Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas, Mehdi Bahri, Yannis Panagakis, Nikolaos Laskaris, Dimitrios A. Adamos, Stefanos Zafeiriou, William C. Duong, Stephen M. Gordon, Vernon J. Lawhern, Maciej Śliwowski, Vincent Rouanne, Piotr Tempczyk
Task 2 is centred on Brain-Computer Interfacing (BCI), addressing motor imagery decoding across both subjects and data sets.
no code implementations • 1 Feb 2022 • Stylianos Bakas, Siegfried Ludwig, Konstantinos Barmpas, Mehdi Bahri, Yannis Panagakis, Nikolaos Laskaris, Dimitrios A. Adamos, Stefanos Zafeiriou
The second task required to transfer models trained on the subjects of one or more source motor imagery datasets to perform inference on two target datasets, providing a small set of personalized calibration data for multiple test subjects.
no code implementations • CVPR 2022 • Rolandos Alexandros Potamias, Stylianos Ploumpis, Stefanos Zafeiriou
Then, we train a sparse attention network to propose candidate triangles based on the edge connectivity of the sampled vertices.
1 code implementation • 11 Dec 2021 • Alexandros Lattas, Stylianos Moschoglou, Stylianos Ploumpis, Baris Gecer, Abhijeet Ghosh, Stefanos Zafeiriou
Nevertheless, to the best of our knowledge, there is no method which can produce render-ready high-resolution 3D faces from "in-the-wild" images and this can be attributed to the: (a) scarcity of available data for training, and (b) lack of robust methodologies that can successfully be applied on very high-resolution data.
no code implementations • 19 Oct 2021 • Siegfried Ludwig, Stylianos Bakas, Dimitrios A. Adamos, Nikolaos Laskaris, Yannis Panagakis, Stefanos Zafeiriou
Patterns of brain activity are associated with different brain processes and can be used to identify different brain states and make behavioral predictions.
1 code implementation • 11 Oct 2021 • Kaihao Zhang, Dongxu Li, Wenhan Luo, Jingyu Liu, Jiankang Deng, Wei Liu, Stefanos Zafeiriou
It is thus unclear how these algorithms perform on public face hallucination datasets.
Ranked #1 on
Image Super-Resolution
on WLFW
no code implementations • 30 Sep 2021 • Rolandos Alexandros Potamias, Giorgos Bouritsas, Stefanos Zafeiriou
In an attempt to alleviate this computational burden, we propose a fast point cloud simplification method by learning to sample salient points.
1 code implementation • 18 Aug 2021 • Jiankang Deng, Jia Guo, Xiang An, Zheng Zhu, Stefanos Zafeiriou
In this workshop, we organize Masked Face Recognition (MFR) challenge and focus on bench-marking deep face recognition methods under the existence of facial masks.
no code implementations • 7 Jul 2021 • Yannis Panagakis, Jean Kossaifi, Grigorios G. Chrysos, James Oldfield, Mihalis A. Nicolaou, Anima Anandkumar, Stefanos Zafeiriou
Tensors, or multidimensional arrays, are data structures that can naturally represent visual data of multiple dimensions.
no code implementations • 6 Jul 2021 • Francesca Babiloni, Ioannis Marras, Filippos Kokkinos, Jiankang Deng, Grigorios Chrysos, Stefanos Zafeiriou
Spatial self-attention layers, in the form of Non-Local blocks, introduce long-range dependencies in Convolutional Neural Networks by computing pairwise similarities among all possible positions.
Ranked #1 on
Face Detection
on WIDER Face (Hard)
no code implementations • CVPR 2022 • Stylianos Ploumpis, Stylianos Moschoglou, Vasileios Triantafyllou, Stefanos Zafeiriou
3D face reconstruction from a single image is a task that has garnered increased interest in the Computer Vision community, especially due to its broad use in a number of applications such as realistic 3D avatar creation, pose invariant face recognition and face hallucination.
no code implementations • CVPR 2021 • Jiankang Deng, Jia Guo, Jing Yang, Alexandros Lattas, Stefanos Zafeiriou
Deep face recognition has achieved remarkable improvements due to the introduction of margin-based softmax loss, in which the prototype stored in the last linear layer represents the center of each class.
no code implementations • 14 Jun 2021 • Dimitrios Kollias, Irene Kotsia, Elnar Hajiyev, Stefanos Zafeiriou
The Affective Behavior Analysis in-the-wild (ABAW2) 2021 Competition is the second -- following the first very successful ABAW Competition held in conjunction with IEEE FG 2020- Competition that aims at automatically analyzing affect.
1 code implementation • 16 May 2021 • Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou
In this paper, we take a radically different approach and harness the power of Generative Adversarial Networks (GANs) and DCNNs in order to reconstruct the facial texture and shape from single images.
7 code implementations • ICLR 2022 • Jia Guo, Jiankang Deng, Alexandros Lattas, Stefanos Zafeiriou
Although tremendous strides have been made in uncontrolled face detection, efficient face detection with a low computation cost as well as high precision remains an open challenge.
Ranked #7 on
Face Detection
on WIDER Face (Medium)
no code implementations • 8 May 2021 • Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Based on this approach, we build FaceBehaviorNet, the first framework for large-scale face analysis, by jointly learning all facial behavior tasks.
Ranked #6 on
Facial Expression Recognition (FER)
on RAF-DB
(Avg. Accuracy metric, using extra
training data)
1 code implementation • 28 Apr 2021 • Michail Tarasiou, Stefanos Zafeiriou
This report presents design considerations for automatically generating satellite imagery datasets for training machine learning models with emphasis placed on dense classification tasks, e. g. semantic segmentation.
2 code implementations • 9 Apr 2021 • Michail Tarasiou, Riza Alp Guler, Stefanos Zafeiriou
For crop type semantic segmentation from Satellite Image Time Series (SITS) we find performance at parcel boundaries to be a critical bottleneck and explain how CSCL tackles the underlying cause of that problem, improving the state-of-the-art performance in this task.
no code implementations • 30 Mar 2021 • Michail Christos Doukas, Mohammad Rami Koujan, Viktoriia Sharmanska, Stefanos Zafeiriou
Head reenactment is an even more challenging task, which aims at transferring not only the facial expression, but also the entire head pose from a source person to a target.
no code implementations • 29 Mar 2021 • Dimitrios Kollias, Stefanos Zafeiriou
Affect analysis and recognition can be seen as a dual knowledge generation problem, involving: i) creation of new, large and rich in-the-wild databases and ii) design and training of novel deep neural architectures that are able to analyse affect over these databases and to successfully generalise their performance on other datasets.
1 code implementation • 4 Mar 2021 • Panagiotis Tzirakis, Anh Nguyen, Stefanos Zafeiriou, Björn W. Schuller
In this paper, we propose a novel framework that can capture both the semantic and the paralinguistic information in the signal.
Speech Emotion Recognition
Sound
Audio and Speech Processing
no code implementations • ICCV 2021 • Francesca Babiloni, Ioannis Marras, Filippos Kokkinos, Jiankang Deng, Grigorios Chrysos, Stefanos Zafeiriou
Spatial self-attention layers, in the form of Non-Local blocks, introduce long-range dependencies in Convolutional Neural Networks by computing pairwise similarities among all possible positions.
1 code implementation • CVPR 2021 • Mehdi Bahri, Gaétan Bahl, Stefanos Zafeiriou
In this paper, we present and evaluate different strategies for the binarization of graph neural networks.
1 code implementation • CVPR 2021 • Baris Gecer, Jiankang Deng, Stefanos Zafeiriou
Many recent 3D facial texture reconstruction and pose manipulation from a single image approaches still rely on large and clean face datasets to train image-to-image Generative Adversarial Networks (GANs).
no code implementations • 16 Dec 2020 • Mehdi Bahri, Eimear O' Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou
Compared to the previous state-of-the-art learning algorithms for non-rigid registration of face scans, SMF only requires the raw data to be rigidly aligned (with scaling) with a pre-defined face template.
no code implementations • ICCV 2021 • Michail Christos Doukas, Stefanos Zafeiriou, Viktoriia Sharmanska
Recent attempts to solve the problem of head reenactment using a single reference image have shown promising results.
no code implementations • ECCV 2020 • Rolandos Alexandros Potamias, Jiali Zheng, Stylianos Ploumpis, Giorgos Bouritsas, Evangelos Ververas, Stefanos Zafeiriou
To this end, in this study we employ a deep mesh encoder-decoder like architecture to synthesize realistic high resolution facial expressions by using a single neutral frame along with an expression identification.
5 code implementations • 20 Jun 2020 • Grigorios Chrysos, Stylianos Moschoglou, Giorgos Bouritsas, Jiankang Deng, Yannis Panagakis, Stefanos Zafeiriou
We introduce three tensor decompositions that significantly reduce the number of parameters and show how they can be efficiently implemented by hierarchical neural networks.
Ranked #1 on
Face Recognition
on CALFW
2 code implementations • 16 Jun 2020 • Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein
It has been shown that the expressive power of standard GNNs is bounded by the Weisfeiler-Leman (WL) graph isomorphism test, from which they inherit proven limitations such as the inability to detect and count graph substructures.
Ranked #2 on
Graph Regression
on ZINC 100k
1 code implementation • 22 May 2020 • Mohammad Rami Koujan, Michail Christos Doukas, Anastasios Roussos, Stefanos Zafeiriou
In this paper, we propose a novel machine learning architecture for facial reenactment.
no code implementations • 22 May 2020 • Mohammad Rami Koujan, Michail Christos Doukas, Anastasios Roussos, Stefanos Zafeiriou
Video-to-video synthesis is a challenging problem aiming at learning a translation function between a sequence of semantic maps and a photo-realistic video depicting the characteristics of a driving video.
1 code implementation • CVPR 2020 • Mohammad Rami Koujan, Anastasios Roussos, Stefanos Zafeiriou
Dense 3D facial motion capture from only monocular in-the-wild pairs of RGB images is a highly challenging problem with numerous applications, ranging from facial expression recognition to facial reenactment.
no code implementations • CVPR 2020 • Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou
Graph convolution operators bring the advantages of deep learning to a variety of graph and mesh processing tasks previously deemed out of reach.
4 code implementations • CVPR 2020 • Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael Bronstein, Stefanos Zafeiriou
We introduce a simple and effective network architecture for monocular 3D hand pose estimation consisting of an image encoder followed by a mesh convolutional decoder that is trained through a direct 3D hand mesh reconstruction loss.
Ranked #25 on
3D Hand Pose Estimation
on FreiHAND
1 code implementation • CVPR 2020 • Alexandros Lattas, Stylianos Moschoglou, Baris Gecer, Stylianos Ploumpis, Vasileios Triantafyllou, Abhijeet Ghosh, Stefanos Zafeiriou
Over the last years, with the advent of Generative Adversarial Networks (GANs), many face analysis tasks have accomplished astounding performance, with applications including, but not limited to, face generation and 3D face reconstruction from a single "in-the-wild" image.
2 code implementations • 8 Mar 2020 • Grigorios G. Chrysos, Stylianos Moschoglou, Giorgos Bouritsas, Yannis Panagakis, Jiankang Deng, Stefanos Zafeiriou
Deep Convolutional Neural Networks (DCNNs) is currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning.
Ranked #1 on
Graph Representation Learning
on COMA
no code implementations • 11 Feb 2020 • Ioannis Marras, Grigorios G. Chrysos, Ioannis Alexiou, Gregory Slabaugh, Stefanos Zafeiriou
Deep Convolutional Neural Networks (CNNs) have been successfully used in many low-level vision problems like image denoising.
no code implementations • 30 Jan 2020 • Dimitrios Kollias, Attila Schulc, Elnar Hajiyev, Stefanos Zafeiriou
For the Challenges, we provide a common benchmark database, Aff-Wild2, which is a large scale in-the-wild database and the first one annotated for all these three tasks.
no code implementations • 29 Nov 2019 • Michail Tarasiou, Stefanos Zafeiriou
Recent developments in computer vision and machine learning have made it possible to create realistic manipulated videos of human faces, raising the issue of ensuring adequate protection against the malevolent effects unlocked by such capabilities.
no code implementations • 24 Nov 2019 • Filippos Kokkinos, Ioannis Marras, Matteo Maggioni, Gregory Slabaugh, Stefanos Zafeiriou
Next, we employ PAFU in deep neural networks as a replacement of standard convolutional layers to enhance the original architectures with spatially varying computations to achieve considerable performance improvements.
1 code implementation • 18 Nov 2019 • Stylianos Ploumpis, Evangelos Ververas, Eimear O' Sullivan, Stylianos Moschoglou, Haoyang Wang, Nick Pears, William A. P. Smith, Baris Gecer, Stefanos Zafeiriou
Eye and eye region models are incorporated into the head model, along with basic models of the teeth, tongue and inner mouth cavity.
1 code implementation • 13 Nov 2019 • Shunwang Gong, Lei Chen, Michael Bronstein, Stefanos Zafeiriou
Intrinsic graph convolution operators with differentiable kernel functions play a crucial role in analyzing 3D shape meshes.
no code implementations • 15 Oct 2019 • Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
We present the first and the largest study of all facial behaviour tasks learned jointly in a single multi-task, multi-domain and multi-label network, which we call FaceBehaviorNet.
no code implementations • 12 Oct 2019 • Kritaphat Songsri-in, Stefanos Zafeiriou
In addition, our proposed method consists of two branches and can coherently predict face forensic detection and localization to outperform the previous state-of-the-art techniques on the newly proposed dataset as well as the faceforecsic++ dataset especially on low-quality videos.
no code implementations • 3 Oct 2019 • Dimitrios Kollias, Stefanos Zafeiriou
This paper presents a novel CNN-RNN based approach, which exploits multiple CNN features for dimensional emotion recognition in-the-wild, utilizing the One-Minute Gradual-Emotion (OMG-Emotion) dataset.
no code implementations • 25 Sep 2019 • Dimitrios Kollias, Stefanos Zafeiriou
The need to collect and annotate diverse in-the-wild datasets has become apparent with the rise of deep learning models, as the default approach to address any computer vision task.
Ranked #9 on
Facial Expression Recognition (FER)
on RAF-DB
(Avg. Accuracy metric)
1 code implementation • ECCV 2020 • Baris Gecer, Alexander Lattas, Stylianos Ploumpis, Jiankang Deng, Athanasios Papaioannou, Stylianos Moschoglou, Stefanos Zafeiriou
In this paper, we present the first methodology that generates high-quality texture, shape, and normals jointly, which can be used for photo-realistic synthesis.
no code implementations • 26 Aug 2019 • Evangelos Ververas, Stefanos Zafeiriou
In particular, we propose the SliderGAN which transforms an input face image into a new one according to the continuous values of a statistical blendshape model of facial motion.
no code implementations • 19 Aug 2019 • Grigorios Chrysos, Stylianos Moschoglou, Yannis Panagakis, Stefanos Zafeiriou
Generative Adversarial Networks (GANs) have become the gold standard when it comes to learning generative models for high-dimensional distributions.
no code implementations • 28 May 2019 • Michail C. Doukas, Viktoriia Sharmanska, Stefanos Zafeiriou
Despite remarkable success in image-to-image translation that celebrates the advancements of generative adversarial networks (GANs), very limited attempts are known for video domain translation.
2 code implementations • ICCV 2019 • Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Michael Bronstein, Stefanos Zafeiriou
Generative models for 3D geometric data arise in many important applications in 3D computer vision and graphics.
1 code implementation • 4 May 2019 • Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael Bronstein, Stefanos Zafeiriou
In this paper, we demonstrate an alternative solution that is based on the idea of encoding images into a latent non-linear representation of meshes.
76 code implementations • 2 May 2019 • Jiankang Deng, Jia Guo, Yuxiang Zhou, Jinke Yu, Irene Kotsia, Stefanos Zafeiriou
Face Analysis Project on MXNet
Ranked #2 on
Face Detection
on WIDER Face (Medium)
no code implementations • 1 May 2019 • Stylianos Moschoglou, Stylianos Ploumpis, Mihalis Nicolaou, Athanasios Papaioannou, Stefanos Zafeiriou
As a result, linear methods such as Principal Component Analysis (PCA) have been mainly utilized towards 3D shape analysis, despite being unable to capture non-linearities and high frequency details of the 3D face - such as eyelid and lip variations.
no code implementations • 25 Apr 2019 • Kritaphat Songsri-in, Stefanos Zafeiriou
In this paper we are concerned with the challenging problem of producing a full image sequence of a deformable face given only an image and generic facial motions encoded by a set of sparse landmarks.
no code implementations • 15 Apr 2019 • Panagiotis Tzirakis, Athanasios Papaioannou, Alexander Lattas, Michail Tarasiou, Björn Schuller, Stefanos Zafeiriou
Synthesising 3D facial motion from speech is a crucial problem manifesting in a multitude of applications such as computer games and movies.
no code implementations • CVPR 2019 • Yuxiang Zhou, Jiankang Deng, Irene Kotsia, Stefanos Zafeiriou
3D Morphable Models (3DMMs) are statistical models that represent facial texture and shape variations using a set of linear bases and more particular Principal Component Analysis (PCA).
no code implementations • 25 Mar 2019 • Shiyang Cheng, Michael Bronstein, Yuxiang Zhou, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou
Generative Adversarial Networks (GANs) are currently the method of choice for generating visual data.
1 code implementation • CVPR 2019 • Stylianos Ploumpis, Haoyang Wang, Nick Pears, William A. P. Smith, Stefanos Zafeiriou
Three-dimensional Morphable Models (3DMMs) are powerful statistical tools for representing the 3D surfaces of an object class.
1 code implementation • CVPR 2019 • Baris Gecer, Stylianos Ploumpis, Irene Kotsia, Stefanos Zafeiriou
In this paper, we take a radically different approach and harness the power of Generative Adversarial Networks (GANs) and DCNNs in order to reconstruct the facial texture and shape from single images.
Ranked #1 on
3D Face Reconstruction
on Florence
(Average 3D Error metric)
3 code implementations • 5 Dec 2018 • Jia Guo, Jiankang Deng, Niannan Xue, Stefanos Zafeiriou
Face Analysis Project on MXNet
Ranked #1 on
Face Alignment
on IBUG
no code implementations • 12 Nov 2018 • Dimitrios Kollias, Shiyang Cheng, Evangelos Ververas, Irene Kotsia, Stefanos Zafeiriou
This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i. e., anger, disgust, fear, joy, sadness and surprise), or in terms of valence (i. e., how positive or negative is an emotion) and arousal (i. e., power of the emotion activation).
Ranked #7 on
Facial Expression Recognition (FER)
on RAF-DB
(Avg. Accuracy metric, using extra
training data)
1 code implementation • 11 Nov 2018 • Dimitrios Kollias, Stefanos Zafeiriou
The obtained results show premise for utilization of the extended Aff-Wild, as well as of the developed deep neural architectures for visual analysis of human behaviour in terms of continuous emotion dimensions.
no code implementations • 11 Nov 2018 • Dimitrios Kollias, Stefanos Zafeiriou
Various approaches have been proposed for: i) discrete emotion recognition in terms of the primary facial expressions; ii) emotion analysis in terms of facial Action Units (AUs), assuming a fixed expression intensity; iii) dimensional emotion analysis, in terms of valence and arousal (VA).
no code implementations • 12 Sep 2018 • Dimitrios Kollias, Stefanos Zafeiriou
A novel procedure is presented in this paper, for training a deep convolutional and recurrent neural network, taking into account both the available training data set and some information extracted from similar networks trained with other relevant data sets.
no code implementations • CVPR 2018 • Shiyang Cheng, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou
The progress we are currently witnessing in many computer vision applications, including automatic face analysis, would not be made possible without tremendous efforts in collecting and annotating large scale visual databases.
Facial Expression Recognition
Facial Expression Recognition (FER)
1 code implementation • ICLR 2019 • Grigorios G. Chrysos, Jean Kossaifi, Stefanos Zafeiriou
Conditional generative adversarial networks (cGAN) have led to large improvements in the task of conditional image generation, which lies at the heart of computer vision.
no code implementations • 3 May 2018 • Dimitrios Kollias, Stefanos Zafeiriou
This paper presents our approach to the One-Minute Gradual-Emotion Recognition (OMG-Emotion) Challenge, focusing on dimensional emotion recognition through visual analysis of the provided emotion videos.
1 code implementation • 29 Apr 2018 • Dimitrios Kollias, Panagiotis Tzirakis, Mihalis A. Nicolaou, Athanasios Papaioannou, Guoying Zhao, Björn Schuller, Irene Kotsia, Stefanos Zafeiriou
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions.
no code implementations • 8 Mar 2018 • Grigorios G. Chrysos, Paolo Favaro, Stefanos Zafeiriou
Notwithstanding, a much less standing mode of variation is motion deblurring, which however presents substantial challenges in face analysis.
no code implementations • CVPR 2017 • Riza Alp Guler, Yuxiang Zhou, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, Iasonas Kokkinos
We define the regression task in terms of the intrinsic, U-V coordinates of a 3D deformable model that is brought into correspondence with image instances at training time.
1 code implementation • 4 Feb 2018 • Panagiotis Tzirakis, Stefanos Zafeiriou, Bjorn W. Schuller
To our knowledge, this is the first toolkit that provides generic end-to-end learning for profiling capabilities in either unimodal or multimodal cases.
100 code implementations • CVPR 2019 • Jiankang Deng, Jia Guo, Jing Yang, Niannan Xue, Irene Kotsia, Stefanos Zafeiriou
Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability.
Ranked #1 on
Face Verification
on Labeled Faces in the Wild
(using extra training data)
no code implementations • 20 Jan 2018 • Niannan Xue, Jiankang Deng, Shiyang Cheng, Yannis Panagakis, Stefanos Zafeiriou
Robust principal component analysis (RPCA) is a powerful method for learning low-rank feature representation of various visual data.
no code implementations • 20 Jan 2018 • Grigorios G. Chrysos, Yannis Panagakis, Stefanos Zafeiriou
In addition, the state-of-the-art data-driven methods demand a vast amount of data, hence a standard engineering trick employed is artificial data augmentation for instance by adding into the data cropped and (affinely) transformed images.
no code implementations • 18 Jan 2018 • Mehdi Bahri, Yannis Panagakis, Stefanos Zafeiriou
Dictionary learning and component analysis models are fundamental for learning compact representations that are relevant to a given task (feature extraction, dimensionality reduction, denoising, etc.).
no code implementations • 15 Dec 2017 • Stylianos Moschoglou, Evangelos Ververas, Yannis Panagakis, Mihalis Nicolaou, Stefanos Zafeiriou
In this paper, we propose a novel component analysis technique that is suitable for facial UV maps containing a considerable amount of missing information and outliers, while additionally, incorporates knowledge from various attributes (such as age and identity).
no code implementations • CVPR 2018 • Jiankang Deng, Shiyang Cheng, Niannan Xue, Yuxiang Zhou, Stefanos Zafeiriou
We demonstrate that by attaching the completed UV to the fitted mesh and generating instances of arbitrary poses, we can increase pose variations for training deep face recognition/verification models, and minimise pose discrepancy during testing, which lead to better performance.
1 code implementation • 5 Dec 2017 • Shiyang Cheng, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou
4DFAB contains recordings of 180 subjects captured in four different sessions spanning over a five-year period.
Facial Expression Recognition
Facial Expression Recognition (FER)
no code implementations • 28 Nov 2017 • Mengjiao Wang, Zhixin Shu, Shiyang Cheng, Yannis Panagakis, Dimitris Samaras, Stefanos Zafeiriou
Several factors contribute to the appearance of an object in a visual scene, including pose, illumination, and deformation, among others.
no code implementations • 14 Sep 2017 • Niannan Xue, Jiankang Deng, Yannis Panagakis, Stefanos Zafeiriou
We revisit the problem of robust principal component analysis with features acting as prior side information.
no code implementations • 23 Aug 2017 • Žiga Emeršič, Dejan Štepec, Vitomir Štruc, Peter Peer, Anjith George, Adil Ahmad, Elshibani Omar, Terrance E. Boult, Reza Safdari, Yuxiang Zhou, Stefanos Zafeiriou, Dogucan Yaman, Fevziye I. Eyiokur, Hazim K. Ekenel
In this paper we present the results of the Unconstrained Ear Recognition Challenge (UERC), a group benchmarking effort centered around the problem of person recognition from ear images captured in uncontrolled conditions.
no code implementations • 20 Aug 2017 • Jiankang Deng, George Trigeorgis, Yuxiang Zhou, Stefanos Zafeiriou
This encompasses two basic problems: i) the detection and deformable fitting steps are performed independently, while the detector might not provide best-suited initialisation for the fitting step, ii) the face appearance varies hugely across different poses, which makes the deformable face fitting very challenging and thus distinct models have to be used (\eg, one for profile and one for frontal faces).
no code implementations • CVPR 2017 • Christos Sagonas, Yannis Panagakis, Alina Leidinger, Stefanos Zafeiriou
Even though the CCA is a powerful tool, it has several drawbacks that render its application challenging for computer vision applications.
no code implementations • CVPR 2017 • Mengjiao Wang, Yannis Panagakis, Patrick Snape, Stefanos Zafeiriou
To extract these modes of variations from visual data, several supervised methods, such as the TensorFaces, that rely on multilinear (tensor) decomposition (e. g., Higher Order SVD) have been developed.
no code implementations • CVPR 2017 • George Trigeorgis, Patrick Snape, Iasonas Kokkinos, Stefanos Zafeiriou
In this work we pursue a data-driven approach to the problem of estimating surface normals from a single intensity image, focusing in particular on human faces.
no code implementations • 27 Apr 2017 • Grigorios G. Chrysos, Stefanos Zafeiriou
Blind deblurring consists a long studied task, however the outcomes of generic methods are not effective in real world blurred images.
2 code implementations • 27 Apr 2017 • Panagiotis Tzirakis, George Trigeorgis, Mihalis A. Nicolaou, Björn Schuller, Stefanos Zafeiriou
The system is then trained in an end-to-end fashion where - by also taking advantage of the correlations of the each of the streams - we manage to significantly outperform the traditional approaches based on auditory and visual handcrafted features for the prediction of spontaneous and natural emotions on the RECOLA database of the AVEC 2016 research challenge on emotion recognition.
1 code implementation • ICCV 2017 • Mehdi Bahri, Yannis Panagakis, Stefanos Zafeiriou
In this paper, we introduce a new robust decomposition of images by combining ideas from sparse dictionary learning and PCP.
no code implementations • ICCV 2017 • Niannan Xue, Yannis Panagakis, Stefanos Zafeiriou
Robust Principal Component Analysis (RPCA) aims at recovering a low-rank subspace from grossly corrupted high-dimensional (often visual) data and is a cornerstone in many machine learning and computer vision applications.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
no code implementations • CVPR 2017 • James Booth, Epameinondas Antonakos, Stylianos Ploumpis, George Trigeorgis, Yannis Panagakis, Stefanos Zafeiriou
In this paper, we propose the first, to the best of our knowledge, "in-the-wild" 3DMM by combining a powerful statistical model of facial shape, which describes both identity and expression, with an "in-the-wild" texture model.
Ranked #3 on
3D Face Reconstruction
on Florence
(Average 3D Error metric)
no code implementations • CVPR 2017 • Riza Alp Güler, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, Iasonas Kokkinos
As such our network can provide useful correspondence information as a stand-alone system, while when used as an initialization for Statistical Deformable Models we obtain landmark localization results that largely outperform the current state-of-the-art on the challenging 300W benchmark.
no code implementations • 1 Dec 2016 • Vladimir Gligorijevic, Yannis Panagakis, Stefanos Zafeiriou
Networks have been a general tool for representing, analyzing, and modeling relational data arising in several domains.
no code implementations • 5 Oct 2016 • Orestis Tsinalis, Paul M. Matthews, Yike Guo, Stefanos Zafeiriou
We used convolutional neural networks (CNNs) for automatic sleep stage scoring based on single-channel electroencephalography (EEG) to learn task-specific filters for classification without using prior domain knowledge.
no code implementations • CVPR 2016 • Yuxiang Zhou, Epameinondas Antonakos, Joan Alabort-i-Medina, Anastasios Roussos, Stefanos Zafeiriou
In this paper, we show for the first time, to the best of our knowledge, that it is possible to construct SDMs by putting object shapes in dense correspondence.
no code implementations • CVPR 2016 • Lazaros Zafeiriou, Epameinondas Antonakos, Stefanos Zafeiriou, Maja Pantic
Typically, the problems of spatial and temporal alignment of sequences are considered disjoint.
no code implementations • CVPR 2016 • George Trigeorgis, Patrick Snape, Mihalis A. Nicolaou, Epameinondas Antonakos, Stefanos Zafeiriou
Cascaded regression has recently become the method of choice for solving non-linear least squares problems such as deformable image alignment.
no code implementations • CVPR 2016 • James Booth, Anastasios Roussos, Stefanos Zafeiriou, Allan Ponniah, David Dunaway
We present Large Scale Facial Model (LSFM) -- a 3D Morphable Model (3DMM) automatically constructed from 9, 663 distinct facial identities.
no code implementations • CVPR 2016 • George Trigeorgis, Mihalis A. Nicolaou, Stefanos Zafeiriou, Bjorn W. Schuller
Thus, they fail to capture complex, hierarchical non-linear representations which may prove to be beneficial towards the task of temporal alignment, particularly when dealing with multi-modal data (e. g., aligning visual and acoustic information).
1 code implementation • 18 Mar 2016 • Grigorios G. Chrysos, Epameinondas Antonakos, Patrick Snape, Akshay Asthana, Stefanos Zafeiriou
Recently, technologies such as face detection, facial landmark localisation and face recognition and verification have matured enough to provide effective and efficient solutions for imagery captured under arbitrary conditions (referred to as "in-the-wild").
no code implementations • 2 Jan 2016 • Joan Alabort-i-Medina, Stefanos Zafeiriou
Active Appearance Models (AAMs) are one of the most popular and well-established techniques for modeling deformable objects in computer vision.
no code implementations • ICCV 2015 • Patrick Snape, Anastasios Roussos, Yannis Panagakis, Stefanos Zafeiriou
In this paper, we propose a method for the robust and efficient computation of multi-frame optical flow in an expressive sequence of facial images.
no code implementations • ICCV 2015 • Christos Sagonas, Yannis Panagakis, Stefanos Zafeiriou, Maja Pantic
The proposed method is assessed in frontal face reconstruction, face landmark localization, pose-invariant face recognition, and face verification in unconstrained conditions.
no code implementations • 18 Sep 2015 • Vahan Hovhannisyan, Panos Parpas, Stefanos Zafeiriou
Composite convex optimization models arise in several applications, and are especially prevalent in inverse problems with a sparsity inducing norm and in general convex optimization with simple constraints.
no code implementations • 10 Sep 2015 • George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou, Bjoern W. Schuller
Semi-Non-negative Matrix Factorization is a technique that learns a low-dimensional representation of a dataset that lends itself to a clustering interpretation.
no code implementations • CVPR 2015 • Joan Alabort-i-Medina, Stefanos Zafeiriou
In this paper we try to marry the previous two frameworks into a unified one that potentially combines the advantages of both.
no code implementations • CVPR 2015 • Epameinondas Antonakos, Joan Alabort-i-Medina, Stefanos Zafeiriou
Inspired by the tree structure used in PS, the proposed Active Pictorial Structures (APS) model the appearance of the object using multiple graph-based pairwise normal distributions (Gaussian Markov Random Field) between the patches extracted from the regions around adjacent landmarks.
no code implementations • CVPR 2015 • Patrick Snape, Yannis Panagakis, Stefanos Zafeiriou
In this paper we propose a method to automatically recover a class specific low dimensional spherical harmonic basis from a set of in-the-wild facial images.
no code implementations • 3 Feb 2015 • Christos Sagonas, Yannis Panagakis, Stefanos Zafeiriou, Maja Pantic
The proposed method is assessed in frontal face reconstruction (pose correction), face landmark localization, and pose-invariant face recognition and verification by conducting experiments on $6$ facial images databases.
no code implementations • CVPR 2014 • Akshay Asthana, Stefanos Zafeiriou, Shiyang Cheng, Maja Pantic
We propose very efficient strategies to update the model and we show that is possible to automatically construct robust discriminative person and imaging condition specific models 'in-the-wild' that outperform state-of-the-art generic face alignment strategies.
no code implementations • CVPR 2014 • Epameinondas Antonakos, Stefanos Zafeiriou
The only requirements of the method are a crude bounding box object detector and a-priori knowledge of the object's shape (e. g. a point distribution model).
no code implementations • CVPR 2014 • Christos Sagonas, Yannis Panagakis, Stefanos Zafeiriou, Maja Pantic
Next, to correct the fittings of a generic model, image congealing (i. e., batch image aliment) is performed by employing only the learnt orthonormal subspace.
no code implementations • CVPR 2014 • Symeon Nikitidis, Stefanos Zafeiriou, Maja Pantic
A key problem often encountered by many learning algorithms in computer vision dealing with high dimensional data is the so called "curse of dimensionality" which arises when the available training samples are less than the input feature space dimensionality.
no code implementations • CVPR 2014 • Stephan Liwicki, Minh-Tri Pham, Stefanos Zafeiriou, Maja Pantic, Bjorn Stenger
In this paper we introduce a new distance for robustly matching vectors of 3D rotations.
no code implementations • CVPR 2014 • Patrick Snape, Stefanos Zafeiriou
We propose a kernel-based framework for computing components from a set of surface normals.
no code implementations • CVPR 2014 • Joan Alabort-i-Medina, Stefanos Zafeiriou
In this paper we provide the first, to the best of our knowledge, Bayesian formulation of one of the most successful and well-studied statistical models of shape and texture, i. e.
no code implementations • CVPR 2013 • Akshay Asthana, Stefanos Zafeiriou, Shiyang Cheng, Maja Pantic
We present a novel discriminative regression based approach for the Constrained Local Models (CLMs) framework, referred to as the Discriminative Response Map Fitting (DRMF) method, which shows impressive performance in the generic face fitting scenario.
no code implementations • CVPR 2013 • Yannis Panagakis, Mihalis A. Nicolaou, Stefanos Zafeiriou, Maja Pantic
The superiority of the proposed method against the state-of-the-art time alignment methods, namely the canonical time warping and the generalized time warping, is indicated by the experimental results on both synthetic and real datasets.
no code implementations • 13 Mar 2013 • Mihalis A. Nicolaou, Stefanos Zafeiriou, Maja Pantic
We present a unifying framework which reduces the construction of probabilistic component analysis techniques to a mere selection of the latent neighbourhood, thus providing an elegant and principled framework for creating novel component analysis models as well as constructing probabilistic equivalents of deterministic component analysis methods.