no code implementations • 13 Feb 2018 • Li Liu, Jie Chen, Guoying Zhao, Paul Fieguth, Xilin Chen, Matti Pietikäinen
Because extreme scale variations are not necessarily present in most standard texture databases, to support the proposed extreme-scale aspects of texture understanding we are developing a new dataset, the Extreme Scale Variation Textures (ESVaT), to test the performance of our framework.
no code implementations • 31 Jan 2018 • Li Liu, Jie Chen, Paul Fieguth, Guoying Zhao, Rama Chellappa, Matti Pietikainen
Texture is a fundamental characteristic of many types of images, and texture representation is one of the essential and challenging problems in computer vision and pattern recognition which has attracted extensive research attention.
no code implementations • 8 Oct 2017 • Xiaopeng Hong, Thuong-Khanh Tran, Guoying Zhao
Micro-expressions are rapid and involuntary facial expressions, which indicate the suppressed or concealed emotions.
no code implementations • 30 Sep 2017 • Lei Tian, Xiaopeng Hong, Guoying Zhao, Chunxiao Fan, Yue Ming, Matti Pietikäinen
Moreover, it is easy to combine other discriminative and robust cues by using the second order pooling.
no code implementations • 26 Jul 2017 • Yuan Zong, Xiaohua Huang, Wenming Zheng, Zhen Cui, Guoying Zhao
In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases.
no code implementations • 2 Nov 2015 • Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen
For ME recognition, the performance of previous studies is low.
no code implementations • 20 Dec 2016 • Matti Pietikäinen, Guoying Zhao
In recent years very discriminative and computationally efficient local texture descriptors based on local binary patterns (LBP) have been developed, which has led to significant progress in applying texture methods to different problems and applications.
no code implementations • 12 Oct 2016 • Xiaohua Huang, Abhinav Dhall, Xin Liu, Guoying Zhao, Jingang Shi, Roland Goecke, Matti Pietikainen
We fuse face, upperbody and scene information for robustness of GER against the challenging environments.
no code implementations • 7 Aug 2016 • Xiaohua Huang, Su-Jing Wang, Xin Liu, Guoying Zhao, Xiaoyi Feng, Matti Pietikainen
For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition.
no code implementations • 4 Aug 2016 • Yingyue Xu, Xiaopeng Hong, Fatih Porikli, Xin Liu, Jie Chen, Guoying Zhao
Previous offline integration methods usually face two challenges: 1. if most of the candidate saliency models misjudge the saliency on an image, the integration result will lean heavily on those inferior candidate models; 2. an unawareness of the ground truth saliency labels brings difficulty in estimating the expertise of each candidate model.
no code implementations • 3 May 2016 • Jing Zhou, Xiaopeng Hong, Fei Su, Guoying Zhao
To overcome this problem, we propose a real-time regression framework based on the recurrent convolutional neural network for automatic frame-level pain intensity estimation.
no code implementations • 15 Apr 2016 • Xiaopeng Hong, Xianbiao Qi, Guoying Zhao, Matti Pietikäinen
Fisher vector (FV) has become a popular image representation.
no code implementations • 8 Sep 2015 • Xianbiao Qi, Guoying Zhao, Jie Chen, Matti Pietikäinen
We validate the GSS pre-processing under the Local Binary Pattern (LBP) and the Bag-of-Words (BoW) frameworks.
no code implementations • 22 Apr 2015 • Xianbiao Qi, Guoying Zhao, Linlin Shen, Qingquan Li, Matti Pietikainen
It is worth to mention that we achieve a 65. 4\% classification accuracy-- which is, to the best of our knowledge, the highest record by far --on Flickr Material Database by using a single feature.
no code implementations • 16 Feb 2015 • Xianbiao Qi, Guoying Zhao, Chun-Guang Li, Jun Guo, Matti Pietikäinen
Indirect Immunofluorescence (IIF) HEp-2 cell image is an effective evidence for diagnosis of autoimmune diseases.
no code implementations • 1 Feb 2015 • Xianbiao Qi, Chun-Guang Li, Guoying Zhao, Xiaopeng Hong, Matti Pietikäinen
Moreover we explore two different implementations of the TCoF scheme, i. e., the \textit{spatial} TCoF and the \textit{temporal} TCoF, in which the mean-removed frames and the difference between two adjacent frames are used as the inputs of the ConvNet, respectively.
no code implementations • 19 Dec 2018 • Yuan Zong, Tong Zhang, Wenming Zheng, Xiaopeng Hong, Chuangao Tang, Zhen Cui, Guoying Zhao
Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis.
no code implementations • 15 Jan 2019 • Zhaoqiang Xia, Xiaopeng Hong, Xingyu Gao, Xiaoyi Feng, Guoying Zhao
To exploit the merits of deep learning, we propose a novel deep recurrent convolutional networks based micro-expression recognition approach, capturing the spatial-temporal deformations of micro-expression sequence.
no code implementations • 23 Jan 2019 • Wei Peng, Xiaopeng Hong, Yingyue Xu, Guoying Zhao
Facial Micro-expression Recognition (MER) distinguishes the underlying emotional states of spontaneous subtle facialexpressions.
Micro Expression Recognition Micro-Expression Recognition +1
no code implementations • CVPR 2014 • Xiaobai Li, Jie Chen, Guoying Zhao, Matti Pietikainen
Heart rate is an important indicator of people's physiological state.
no code implementations • 7 May 2019 • Muzammil Behzad, Nhat Vo, Xiaobai Li, Guoying Zhao
This paper proposes a novel 4D Facial Expression Recognition (FER) method using Collaborative Cross-domain Dynamic Image Network (CCDN).
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 10 Jul 2019 • Wei Peng, Xiaopeng Hong, Guoying Zhao
Deep neural networks have achieved great success for video analysis and understanding.
no code implementations • 11 Jul 2019 • Yante Li, Xiaohua Huang, Guoying Zhao
In this paper, we focus on AU detection in micro-expressions.
no code implementations • 11 Oct 2019 • Muzammil Behzad, Nhat Vo, Xiaobai Li, Guoying Zhao
We propose a novel landmarks-assisted collaborative end-to-end deep framework for automatic 4D FER.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 8 Feb 2020 • Muzammil Behzad, Nhat Vo, Xiaobai Li, Guoying Zhao
Importantly, we then present a sparsity-aware deep network to compute the sparse representations of convolutional features over multi-views.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 12 Feb 2020 • Mohammad Sabokrou, Masoud Pourreza, Xiaobai Li, Mahmood Fathy, Guoying Zhao
In this paper, we propose a simple yet efficient approach to benefit the advantages of the Deep Neural Network (DNN) by simplifying HR estimation from a complex task to learning from very correlated representation to HR.
no code implementations • 26 Mar 2020 • Xiaobai Li, Hu Han, Hao Lu, Xuesong Niu, Zitong Yu, Antitza Dantcheva, Guoying Zhao, Shiguang Shan
Remote measurement of physiological signals from videos is an emerging topic.
no code implementations • 26 Apr 2020 • Zitong Yu, Xiaobai Li, Xuesong Niu, Jingang Shi, Guoying Zhao
Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e. g., remote healthcare).
no code implementations • 17 Jun 2020 • Zhaoqiang Xia, Wei Peng, Huai-Qian Khor, Xiaoyi Feng, Guoying Zhao
In this paper, we analyze the influence of learning complexity, including the input complexity and model complexity, and discover that the lower-resolution input data and shallower-architecture model are helpful to ease the degradation of deep models in composite-database task.
Micro Expression Recognition Micro-Expression Recognition +1
no code implementations • ECCV 2020 • Zitong Yu, Xiaobai Li, Xuesong Niu, Jingang Shi, Guoying Zhao
In this paper we rephrase face anti-spoofing as a material recognition problem and combine it with classical human material perception [1], intending to extract discriminative and robust features for FAS.
no code implementations • 24 Jul 2020 • Thuong-Khanh Tran, Quang-Nhat Vo, Xiaopeng Hong, Xiaobai Li, Guoying Zhao
Micro-expressions (MEs) are brief and involuntary facial expressions that occur when people are trying to hide their true feelings or conceal their emotions.
no code implementations • 30 Jul 2020 • Wei Peng, Jingang Shi, Zhaoqiang Xia, Guoying Zhao
In human action recognition, current works introduce a dynamic graph generation mechanism to better capture the underlying semantic skeleton connections and thus improves the performance.
Ranked #44 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • 10 Aug 2020 • Haoyu Chen, Zitong Yu, Xin Liu, Wei Peng, Yoon Lee, Guoying Zhao
To address the problem of training on small datasets for action recognition tasks, most prior works are either based on a large number of training samples or require pre-trained models transferred from other large datasets to tackle overfitting problems.
no code implementations • 3 Nov 2020 • Zitong Yu, Jun Wan, Yunxiao Qin, Xiaobai Li, Stan Z. Li, Guoying Zhao
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems.
no code implementations • 14 Dec 2020 • Yanying Liang, Wei Peng, Zhu-Jun Zheng, Olli Silvén, Guoying Zhao
In this paper, a novel hybrid quantum-classical neural network with deep residual learning (Res-HQCNN) is proposed.
no code implementations • 29 Mar 2021 • Yang Liu, Xingming Zhang, Yante Li, Jinzhao Zhou, Xin Li, Guoying Zhao
As far as we know, this is the first survey of graph-based FAA methods.
no code implementations • 15 Apr 2021 • Zitong Yu, Xiaobai Li, Pichao Wang, Guoying Zhao
3D mask face presentation attack detection (PAD) plays a vital role in securing face recognition systems from emergent 3D mask attacks.
no code implementations • 18 May 2021 • Ruijing Yang, Ziyu Guan, Zitong Yu, Xiaoyi Feng, Jinye Peng, Guoying Zhao
The framework is able to capture both local and long-range dependencies via the proposed attention mechanism for the learned appearance representations, which are further enriched by temporally attended physiological cues (remote photoplethysmography, rPPG) that are recovered from videos in the auxiliary task.
no code implementations • 6 Jul 2021 • Yante Li, Jinsheng Wei, Yang Liu, Janne Kauttonen, Guoying Zhao
In this survey, we provide a comprehensive review of deep micro-expression recognition (MER), including datasets, deep MER pipeline, and the bench-marking of most influential methods.
no code implementations • ICLR 2022 • Mozhgan PourKeshavarzi, Guoying Zhao, Mohammad Sabokrou
In this paper, we shed light on an on-call transfer set to provide past experiences whenever a new task arises in the data stream.
no code implementations • 10 Dec 2021 • Liangfei Zhang, Xiaopeng Hong, Ognjen Arandjelovic, Guoying Zhao
Being spontaneous, micro-expressions are useful in the inference of a person's true emotions even if an attempt is made to conceal them.
Micro Expression Recognition Micro-Expression Recognition +1
no code implementations • 21 Dec 2021 • Zitong Yu, Jukka Komulainen, Xiaobai Li, Guoying Zhao
Face presentation attack detection (PAD) has received increasing attention ever since the vulnerabilities to spoofing have been widely recognized.
no code implementations • 3 Jan 2022 • Hanlin Mo, Hua Li, Guoying Zhao
Then, we design a structural framework to generate Gaussian-Hermite moment invariants for these two transform models systematically.
no code implementations • CVPR 2022 • Wei Peng, Li Feng, Guoying Zhao, Fang Liu
While most of these methods focus on designing novel reconstruction networks or new training strategies for a given undersampling pattern, e. g., Cartesian undersampling or Non-Cartesian sampling, to date, there is limited research aiming to learn and optimize k-space sampling strategies using deep neural networks.
no code implementations • 23 Apr 2022 • Yang Liu, Xingming Zhang, Janne Kauttonen, Guoying Zhao
High-quality annotated images are significant to deep facial expression recognition (FER) methods.
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • 1 May 2022 • Jinsheng Wei, Wei Peng, Guanming Lu, Yante Li, Jingjie Yan, Guoying Zhao
However, the discriminability of facial landmarks for MER is unclear.
Micro Expression Recognition Micro-Expression Recognition +1
no code implementations • 11 Oct 2022 • Yante Li, Yang Liu, KhÁnh Nguyen, Henglin Shi, Eija Vuorenmaa, Sanna Jarvela, Guoying Zhao
Collaborative learning is an educational approach that enhances learning through shared goals and working together.
no code implementations • 21 Nov 2022 • Hanlin Mo, Guoying Zhao
Using MNIST dataset, we first evaluate the rotation invariance of RIC-CNN and compare its performance with most of existing rotation-invariant CNN models.
no code implementations • 14 Dec 2022 • Yang Liu, Xingming Zhang, Janne Kauttonen, Guoying Zhao
Specifically, a confidence estimation block and a weighted regularization module are applied to highlight solid samples and suppress uncertain samples in every batch.
1 code implementation • 7 Jan 2023 • Kevin H. M. Cheng, Xu Cheng, Guoying Zhao
However, this approach results in a large feature dimension, and the trained classification layer is required for comparing probe samples, which limits the introduction of new classes.
no code implementations • 7 Feb 2023 • Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Yawen Cui, Jiehua Zhang, Philip Torr, Guoying Zhao
As key modules in PhysFormer, the temporal difference transformers first enhance the quasi-periodic rPPG features with temporal difference guided global attention, and then refine the local spatio-temporal representation against interference.
no code implementations • 3 Mar 2023 • Jinsheng Wei, Haoyu Chen, Guanming Lu, Jingjie Yan, Yue Xie, Guoying Zhao
To solve this issue, driven by the prior information that the category of ME can be inferred by the relationship between the actions of facial different components, this work designs a novel model that can conform to this prior information and learn ME movement features in an interpretable way.
Graph Representation Learning Micro Expression Recognition +1
no code implementations • 25 Mar 2023 • Hanlin Mo, Hongxiang Hao, Guoying Zhao
Further, we achieve their invariance to similarity transform.
no code implementations • 23 May 2023 • Hanlin Mo, Guoying Zhao
The topic of achieving rotational invariance in convolutional neural networks (CNNs) has gained considerable attention recently, as this invariance is crucial for many computer vision tasks such as image classification and matching.
no code implementations • ICCV 2023 • Hao Yu, Xu Cheng, Wei Peng, Weihao Liu, Guoying Zhao
Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-modality discrepancies and intra-class variations.
no code implementations • 16 Oct 2023 • Ling Zhou, Mingpei Wang, Xiaohua Huang, Wenming Zheng, Qirong Mao, Guoying Zhao
Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments.
no code implementations • 19 Feb 2024 • Marko Savic, Guoying Zhao
Remote photoplethysmography (rPPG) is a promising technology that consists of contactless measuring of cardiac activity from facial videos.
no code implementations • 13 Mar 2024 • Tuomas Varanka, Tapani Toivonen, Soumya Tripathy, Guoying Zhao, Erman Acar
In our approach a restoration model is personalized using a few images of the identity, leading to tailored restoration with respect to the identity while retaining fine-grained details.
no code implementations • 2 Apr 2024 • Haoyu Chen, Hao Tang, Ehsan Adeli, Guoying Zhao
This work is driven by the intuition that the robustness of the model can be enhanced by introducing adversarial samples into the training, leading to a more invulnerable model to the noisy inputs, which even can be further extended to directly handling the real-world data like raw point clouds/scans without intermediate processing.
no code implementations • 10 Apr 2024 • Tianming Cai, Guoying Zhao, Junbin Zang, Chen Zong, Zhidong Zhang, Chenyang Xue
Then, multi-dimensional time series are re-embedded, and TDA is applied to obtain topological feature information.
no code implementations • 17 Apr 2024 • Hanlin Mo, Guoying Zhao
Based on various types of non-learnable operators, including gradient, sort, local binary pattern, maximum, etc., this paper designs a set of new convolution operations that are natually invariant to arbitrary rotations.
1 code implementation • ICCV 2019 • Yingyue Xu, Dan Xu, Xiaopeng Hong, Wanli Ouyang, Rongrong Ji, Min Xu, Guoying Zhao
We formulate the CRF graphical model that involves message-passing of feature-feature, feature-prediction, and prediction-prediction, from the coarse scale to the finer scale, to update the features and the corresponding predictions.
1 code implementation • 24 Nov 2020 • Zitong Yu, Xiaobai Li, Jingang Shi, Zhaoqiang Xia, Guoying Zhao
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the presentation attacks (PAs).
1 code implementation • Neural Networks 2022 • Li Ji, Qinghui Zhu, Yongqin Zhang, Juanjuan Yin, Ruyi Wei, Jinsheng Xiao, Deqiang Xiao, Guoying Zhao
Single image super-resolution is an ill-posed problem, whose purpose is to acquire a high-resolution image from its degraded observation.
1 code implementation • 14 Dec 2021 • Haoyu Chen, Hao Tang, Zitong Yu, Nicu Sebe, Guoying Zhao
Specifically, we propose a novel geometry-contrastive Transformer that has an efficient 3D structured perceiving ability to the global geometric inconsistencies across the given meshes.
1 code implementation • 21 Nov 2022 • Tuomas Varanka, Yante Li, Wei Peng, Guoying Zhao
Micro-expressions have drawn increasing interest lately due to various potential applications.
1 code implementation • ICCV 2021 • Haoyu Chen, Hao Tang, Henglin Shi, Wei Peng, Nicu Sebe, Guoying Zhao
With the strength of deep generative models, 3D pose transfer regains intensive research interests in recent years.
1 code implementation • 20 Oct 2021 • Haoyu Chen, Hao Tang, Nicu Sebe, Guoying Zhao
Instead, we introduce AniFormer, a novel Transformer-based architecture, that generates animated 3D sequences by directly taking the raw driving sequences and arbitrary same-type target meshes as inputs.
1 code implementation • 14 Apr 2021 • Lukas Stappen, Alice Baird, Lukas Christ, Lea Schumann, Benjamin Sertolli, Eva-Maria Messner, Erik Cambria, Guoying Zhao, Björn W. Schuller
Multimodal Sentiment Analysis (MuSe) 2021 is a challenge focusing on the tasks of sentiment and emotion, as well as physiological-emotion and emotion-based stress recognition through more comprehensively integrating the audio-visual, language, and biological signal modalities.
1 code implementation • 16 Feb 2022 • Zitong Yu, Ajian Liu, Chenxu Zhao, Kevin H. M. Cheng, Xu Cheng, Guoying Zhao
Can we train a unified model, and flexibly deploy it under various modality scenarios?
1 code implementation • 21 Aug 2020 • Zitong Yu, Benjia Zhou, Jun Wan, Pichao Wang, Haoyu Chen, Xin Liu, Stan Z. Li, Guoying Zhao
Gesture recognition has attracted considerable attention owing to its great potential in applications.
1 code implementation • CVPR 2017 • Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, Qixiang Ye
By stacking RUs in a deep-to-shallow manner, SRN exploits the 'flow' of errors among multiple scales to ease the problems of fitting complex outputs with limited layers, suppressing the complex backgrounds, and effectively matching object symmetry of different scales.
1 code implementation • 17 Jul 2018 • Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, Qixiang Ye
The end-to-end deep learning approach, referred to as a side-output residual network (SRN), leverages the output residual units (RUs) to fit the errors between the object ground-truth symmetry and the side-outputs of multiple stages.
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.
1 code implementation • ECCV 2020 • Xuesong Niu, Zitong Yu, Hu Han, Xiaobai Li, Shiguang Shan, Guoying Zhao
Remote physiological measurements, e. g., remote photoplethysmography (rPPG) based heart rate (HR), heart rate variability (HRV) and respiration frequency (RF) measuring, are playing more and more important roles under the application scenarios where contact measurement is inconvenient or impossible.
1 code implementation • CVPR 2022 • Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao
Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applications (e. g., remote healthcare and affective computing).
3 code implementations • 18 Apr 2023 • Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, JianHua Tao
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
2 code implementations • 26 Apr 2024 • Zheng Lian, Haiyang Sun, Licai Sun, Zhuofan Wen, Siyuan Zhang, Shun Chen, Hao Gu, Jinming Zhao, Ziyang Ma, Xie Chen, Jiangyan Yi, Rui Liu, Kele Xu, Bin Liu, Erik Cambria, Guoying Zhao, Björn W. Schuller, JianHua Tao
In addition to expanding the dataset size, we introduce a new track around open-vocabulary emotion recognition.
2 code implementations • ICCV 2019 • Zitong Yu, Wei Peng, Xiaobai Li, Xiaopeng Hong, Guoying Zhao
The method includes two parts: 1) a Spatio-Temporal Video Enhancement Network (STVEN) for video enhancement, and 2) an rPPG network (rPPGNet) for rPPG signal recovery.
Heart rate estimation Photoplethysmography (PPG) heart rate estimation +2
1 code implementation • 11 Nov 2019 • Wei Peng, Xiaopeng Hong, Haoyu Chen, Guoying Zhao
Human action recognition from skeleton data, fueled by the Graph Convolutional Network (GCN), has attracted lots of attention, due to its powerful capability of modeling non-Euclidean structure data.
2 code implementations • 12 Jan 2021 • Wei Peng, Tuomas Varanka, Abdelrahman Mostafa, Henglin Shi, Guoying Zhao
Recently, there has been a rising surge of momentum for deep representation learning in hyperbolic spaces due to theirhigh capacity of modeling data like knowledge graphs or synonym hierarchies, possessing hierarchical structure.
2 code implementations • 7 May 2019 • Zitong Yu, Xiaobai Li, Guoying Zhao
Recent studies demonstrated that the average heart rate (HR) can be measured from facial videos based on non-contact remote photoplethysmography (rPPG).
3 code implementations • 28 Jun 2021 • Zitong Yu, Yunxiao Qin, Xiaobai Li, Chenxu Zhao, Zhen Lei, Guoying Zhao
Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs).
6 code implementations • CVPR 2020 • Zitong Yu, Chenxu Zhao, Zezheng Wang, Yunxiao Qin, Zhuo Su, Xiaobai Li, Feng Zhou, Guoying Zhao
Here we propose a novel frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information.
Ranked #4 on Face Anti-Spoofing on OULU-NPU
1 code implementation • 17 Apr 2020 • Zitong Yu, Yunxiao Qin, Xiaobai Li, Zezheng Wang, Chenxu Zhao, Zhen Lei, Guoying Zhao
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks.
1 code implementation • 4 May 2021 • Zitong Yu, Yunxiao Qin, Hengshuang Zhao, Xiaobai Li, Guoying Zhao
In this paper, we propose two Cross Central Difference Convolutions (C-CDC), which exploit the difference of the center and surround sparse local features from the horizontal/vertical and diagonal directions, respectively.