Search Results for author:
Found 85 papers, 25 papers with code
Achieving Rotation Invariance in Convolution Operations: Shifting from Data-Driven to Mechanism-Assured
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.
Topological Feature Search Method for Multichannel EEG: Application in ADHD classification
Then, multi-dimensional time series are re-embedded, and TDA is applied to obtain topological feature information.
Towards Robust 3D Pose Transfer with Adversarial Learning
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.
PFStorer: Personalized Face Restoration and Super-Resolution
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.
PhySU-Net: Long Temporal Context Transformer for rPPG with Self-Supervised Pre-training
Remote photoplethysmography (rPPG) is a promising technology that consists of contactless measuring of cardiac activity from facial videos.
An Empirical Study of Super-resolution on Low-resolution Micro-expression Recognition
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.
Modality Unifying Network for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-modality discrepancies and intra-class variations.
Sorted Convolutional Network for Achieving Continuous Rotational Invariance
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.
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
Image Moment Invariants to Rotational Motion Blur
Further, we achieve their invariance to similarity transform.
Prior Information based Decomposition and Reconstruction Learning for Micro-Expression Recognition
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
PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer
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.
Advancing 3D finger knuckle recognition via deep feature learning
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.
Uncertain Facial Expression Recognition via Multi-task Assisted Correction
Specifically, a confidence estimation block and a weighted regularization module are applied to highlight solid samples and suppress uncertain samples in every batch.
Data Leakage and Evaluation Issues in Micro-Expression Analysis
Micro-expressions have drawn increasing interest lately due to various potential applications.
RIC-CNN: Rotation-Invariant Coordinate Convolutional Neural Network
Using MNIST dataset, we first evaluate the rotation invariance of RIC-CNN and compare its performance with most of existing rotation-invariant CNN models.
Exploring Interactions and Regulations in Collaborative Learning: An Interdisciplinary Multimodal Dataset
Collaborative learning is an educational approach that enhances learning through shared goals and working together.
Cross-domain heterogeneous residual network for single image super-resolution
Single image super-resolution is an ill-posed problem, whose purpose is to acquire a high-resolution image from its degraded observation.
Geometric Graph Representation with Learnable Graph Structure and Adaptive AU Constraint for Micro-Expression Recognition
However, the discriminability of facial landmarks for MER is unclear.
Micro Expression Recognition
Micro-Expression Recognition
+1
Uncertain Label Correction via Auxiliary Action Unit Graphs for Facial Expression Recognition
High-quality annotated images are significant to deep facial expression recognition (FER) methods.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks
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.
Flexible-Modal Face Anti-Spoofing: A Benchmark
Can we train a unified model, and flexibly deploy it under various modality scenarios?
Gaussian-Hermite Moment Invariants of General Multi-Channel Functions
Then, we design a structural framework to generate Gaussian-Hermite moment invariants for these two transform models systematically.
Review of Face Presentation Attack Detection Competitions
Face presentation attack detection (PAD) has received increasing attention ever since the vulnerabilities to spoofing have been widely recognized.
Geometry-Contrastive Transformer for Generalized 3D Pose Transfer
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.
Short and Long Range Relation Based Spatio-Temporal Transformer for Micro-Expression Recognition
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
PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer
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).
AniFormer: Data-driven 3D Animation with Transformer
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.
Looking Back on Learned Experiences For Class/task Incremental Learning
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.
Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer
With the strength of deep generative models, 3D pose transfer regains intensive research interests in recent years.
Deep Learning for Micro-expression Recognition: A Survey
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.
Deep Learning for Face Anti-Spoofing: A Survey
Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs).
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
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.
Dual-Cross Central Difference Network for Face Anti-Spoofing
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.
TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection
3D mask face presentation attack detection (PAD) plays a vital role in securing face recognition systems from emergent 3D mask attacks.
The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress
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.
Graph-based Facial Affect Analysis: A Review
As far as we know, this is the first survey of graph-based FAA methods.
Hyperbolic Deep Neural Networks: A Survey
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.
A hybrid quantum-classical neural network with deep residual learning
In this paper, a novel hybrid quantum-classical neural network with deep residual learning (Res-HQCNN) is proposed.
Revisiting Pixel-Wise Supervision for Face Anti-Spoofing
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the presentation attacks (PAs).
NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems.
Searching Multi-Rate and Multi-Modal Temporal Enhanced Networks for Gesture Recognition
Gesture recognition has attracted considerable attention owing to its great potential in applications.
2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework
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.
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition
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
Micro-expression spotting: A new benchmark
Micro-expressions (MEs) are brief and involuntary facial expressions that occur when people are trying to hide their true feelings or conceal their emotions.
Video-based Remote Physiological Measurement via Cross-verified Feature Disentangling
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.
Face Anti-Spoofing with Human Material Perception
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.
Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition
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
AutoHR: A Strong End-to-end Baseline for Remote Heart Rate Measurement with Neural Searching
Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e. g., remote healthcare).
Multi-Modal Face Anti-Spoofing Based on Central Difference Networks
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks.
The 1st Challenge on Remote Physiological Signal Sensing (RePSS)
Remote measurement of physiological signals from videos is an emerging topic.
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
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
Deep-HR: Fast Heart Rate Estimation from Face Video Under Realistic Conditions
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.
Towards Reading Beyond Faces for Sparsity-Aware 4D Affect Recognition
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)
Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching
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.
Landmarks-assisted Collaborative Deep Framework for Automatic 4D Facial Expression Recognition
We propose a novel landmarks-assisted collaborative end-to-end deep framework for automatic 4D FER.
Facial Expression Recognition
Facial Expression Recognition (FER)
Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection
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.
Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement
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
Micro-expression Action Unit Detection with Spatio-temporal Adaptive Pooling
In this paper, we focus on AU detection in micro-expressions.
Video Action Recognition Via Neural Architecture Searching
Deep neural networks have achieved great success for video analysis and understanding.
Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks
Recent studies demonstrated that the average heart rate (HR) can be measured from facial videos based on non-contact remote photoplethysmography (rPPG).
Automatic 4D Facial Expression Recognition via Collaborative Cross-domain Dynamic Image Network
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)
A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework
Facial Micro-expression Recognition (MER) distinguishes the underlying emotional states of spontaneous subtle facialexpressions.
Micro Expression Recognition
Micro-Expression Recognition
+1
Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions
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.
Cross-Database Micro-Expression Recognition: A Benchmark
Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis.
SRN: Side-output Residual Network for Object Reflection Symmetry Detection and Beyond
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.
Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions.
Texture Classification in Extreme Scale Variations using GANet
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.
From BoW to CNN: Two Decades of Texture Representation for Texture Classification
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.
Micro-Expression Spotting: A Benchmark
Micro-expressions are rapid and involuntary facial expressions, which indicate the suppressed or concealed emotions.
PCANet-II: When PCANet Meets the Second Order Pooling
Moreover, it is easy to combine other discriminative and robust cues by using the second order pooling.
Learning a Target Sample Re-Generator for Cross-Database Micro-Expression Recognition
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.
SRN: Side-output Residual Network for Object Symmetry Detection in the Wild
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.
Two decades of local binary patterns: A survey
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.
Analyzing the Affect of a Group of People Using Multi-modal Framework
We fuse face, upperbody and scene information for robustness of GER against the challenging environments.
Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection
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.
Saliency Integration: An Arbitrator Model
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.
Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Video
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.
Probing the Intra-Component Correlations within Fisher Vector for Material Classification
Fisher vector (FV) has become a popular image representation.
Towards Reading Hidden Emotions: A comparative Study of Spontaneous Micro-expression Spotting and Recognition Methods
For ME recognition, the performance of previous studies is low.
HEp-2 Cell Classification: The Role of Gaussian Scale Space Theory as A Pre-processing Approach
We validate the GSS pre-processing under the Local Binary Pattern (LBP) and the Bag-of-Words (BoW) frameworks.
LOAD: Local Orientation Adaptive Descriptor for Texture and Material Classification
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.
HEp-2 Cell Classification via Fusing Texture and Shape Information
Indirect Immunofluorescence (IIF) HEp-2 cell image is an effective evidence for diagnosis of autoimmune diseases.
Dynamic texture and scene classification by transferring deep image features
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.
Remote Heart Rate Measurement From Face Videos Under Realistic Situations
Heart rate is an important indicator of people's physiological state.
