Search Results for author: Weihong Deng

Found 51 papers, 14 papers with code

Generate to Adapt: Resolution Adaption Network for Surveillance Face Recognition

no code implementations ECCV 2020 Han Fang, Weihong Deng, Yaoyao Zhong, Jiani Hu

Although deep learning techniques have largely improved face recognition, unconstrained surveillance face recognition (FR) is still an unsolved challenge, due to the limited training data and the gap of domain distribution.

Face Recognition Translation

Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition

1 code implementation21 Jul 2022 Yuhang Zhang, Chengrui Wang, Xu Ling, Weihong Deng

We find that FER models remember noisy samples by focusing on a part of the features that can be considered related to the noisy labels instead of learning from the whole features that lead to the latent truth.

 Ranked #1 on Facial Expression Recognition on FERPlus (using extra training data)

Facial Expression Recognition Learning with noisy labels

Exploring Disentangled Content Information for Face Forgery Detection

no code implementations19 Jul 2022 Jiahao Liang, Huafeng Shi, Weihong Deng

Convolutional neural network based face forgery detection methods have achieved remarkable results during training, but struggled to maintain comparable performance during testing.

Disentanglement

DH-AUG: DH Forward Kinematics Model Driven Augmentation for 3D Human Pose Estimation

1 code implementation19 Jul 2022 Linzhi Huang, Jiahao Liang, Weihong Deng

To solve this problem, we propose a pose augmentation solution via DH forward kinematics model, which we call DH-AUG. We observe that the previous work is all based on single-frame pose augmentation, if it is directly applied to video pose estimator, there will be several previously ignored problems: (i) angle ambiguity in bone rotation (multiple solutions); (ii) the generated skeleton video lacks movement continuity.

3D Human Pose Estimation

Identifying Rhythmic Patterns for Face Forgery Detection and Categorization

no code implementations4 Jul 2022 Jiahao Liang, Weihong Deng

Motivated by this key observation, we propose a framework for face forgery detection and categorization consisting of: 1) a Spatial-Temporal Filtering Network (STFNet) for PPG signals filtering, and 2) a Spatial-Temporal Interaction Network (STINet) for constraint and interaction of PPG signals.

Boosting Facial Expression Recognition by A Semi-Supervised Progressive Teacher

no code implementations28 May 2022 Jing Jiang, Weihong Deng

On the one hand, PT introduces semi-supervised learning method to relieve the shortage of data in FER.

Facial Expression Recognition

Deep face recognition with clustering based domain adaptation

no code implementations27 May 2022 Mei Wang, Weihong Deng

Despite great progress in face recognition tasks achieved by deep convolution neural networks (CNNs), these models often face challenges in real world tasks where training images gathered from Internet are different from test images because of different lighting condition, pose and image quality.

Domain Adaptation Face Recognition

Cycle Label-Consistent Networks for Unsupervised Domain Adaptation

no code implementations27 May 2022 Mei Wang, Weihong Deng

The cycle label-consistent loss reinforces the consistency between ground-truth labels and pseudo-labels of source samples leading to statistically similar latent representations between source and target domains.

Unsupervised Domain Adaptation

OPOM: Customized Invisible Cloak towards Face Privacy Protection

1 code implementation24 May 2022 Yaoyao Zhong, Weihong Deng

In this paper, we investigate the face privacy protection from a technology standpoint based on a new type of customized cloak, which can be applied to all the images of a regular user, to prevent malicious face recognition systems from uncovering their identity.

Face Recognition

Oracle-MNIST: a Realistic Image Dataset for Benchmarking Machine Learning Algorithms

1 code implementation19 May 2022 Mei Wang, Weihong Deng

We introduce the Oracle-MNIST dataset, comprising of 28$\times $28 grayscale images of 30, 222 ancient characters from 10 categories, for benchmarking pattern classification, with particular challenges on image noise and distortion.

BIG-bench Machine Learning

Unsupervised Structure-Texture Separation Network for Oracle Character Recognition

1 code implementation13 May 2022 Mei Wang, Weihong Deng, Cheng-Lin Liu

Second, transformation is achieved via swapping the learned textures across domains and a classifier for final classification is trained to predict the labels of the transformed scanned characters.

Disentanglement Unsupervised Domain Adaptation

Meta Balanced Network for Fair Face Recognition

no code implementations13 May 2022 Mei Wang, Yaobin Zhang, Weihong Deng

Finally, to mitigate the algorithmic bias, we propose a novel meta-learning algorithm, called Meta Balanced Network (MBN), which learns adaptive margins in large margin loss such that the model optimized by this loss can perform fairly across people with different skin tones.

Face Recognition Meta-Learning

Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing

1 code implementation CVPR 2022 Zhuo Wang, Zezheng Wang, Zitong Yu, Weihong Deng, Jiahong Li, Tingting Gao, Zhongyuan Wang

A novel Shuffled Style Assembly Network (SSAN) is proposed to extract and reassemble different content and style features for a stylized feature space.

Contrastive Learning Domain Generalization +1

Augmented Geometric Distillation for Data-Free Incremental Person ReID

no code implementations CVPR 2022 Yichen Lu, Mei Wang, Weihong Deng

On this basis, we reveal a "noisy distillation" problem stemming from the noise in dreaming memory, and further propose to augment distillation in a pairwise and cross-wise pattern over different views of memory to mitigate it.

Incremental Learning Person Re-Identification

Federated Learning for Face Recognition with Gradient Correction

no code implementations14 Dec 2021 Yifan Niu, Weihong Deng

With increasing appealing to privacy issues in face recognition, federated learning has emerged as one of the most prevalent approaches to study the unconstrained face recognition problem with private decentralized data.

Face Recognition Federated Learning

Relative Uncertainty Learning for Facial Expression Recognition

1 code implementation NeurIPS 2021 Yuhang Zhang, Chengrui Wang, Weihong Deng

To quantify these uncertainties and achieve good performance under noisy data, we regard uncertainty as a relative concept and propose an innovative uncertainty learning method called Relative Uncertainty Learning (RUL).

Facial Expression Recognition

MLFW: A Database for Face Recognition on Masked Faces

no code implementations13 Sep 2021 Chengrui Wang, Han Fang, Yaoyao Zhong, Weihong Deng

As more and more people begin to wear masks due to current COVID-19 pandemic, existing face recognition systems may encounter severe performance degradation when recognizing masked faces.

Face Recognition

Representative Forgery Mining for Fake Face Detection

1 code implementation CVPR 2021 Chengrui Wang, Weihong Deng

Although vanilla Convolutional Neural Network (CNN) based detectors can achieve satisfactory performance on fake face detection, we observe that the detectors tend to seek forgeries on a limited region of face, which reveals that the detectors is short of understanding of forgery.

Data Augmentation Face Detection

Identity-Aware CycleGAN for Face Photo-Sketch Synthesis and Recognition

no code implementations30 Mar 2021 Yuke Fang, Jiani Hu, Weihong Deng

Face photo-sketch synthesis and recognition has many applications in digital entertainment and law enforcement.

Image Generation Sketch Recognition

Face Transformer for Recognition

2 code implementations27 Mar 2021 Yaoyao Zhong, Weihong Deng

Therefore, we investigate the performance of Transformer models in face recognition.

Face Recognition

Selective Pseudo-Labeling with Reinforcement Learning for Semi-Supervised Domain Adaptation

no code implementations7 Dec 2020 Bingyu Liu, Yuhong Guo, Jieping Ye, Weihong Deng

Inspired by the effectiveness of pseudo-labels in domain adaptation, we propose a reinforcement learning based selective pseudo-labeling method for semi-supervised domain adaptation.

Q-Learning reinforcement-learning +1

Point Adversarial Self Mining: A Simple Method for Facial Expression Recognition

no code implementations26 Aug 2020 Ping Liu, Yuewei Lin, Zibo Meng, Lu Lu, Weihong Deng, Joey Tianyi Zhou, Yi Yang

In this paper, we propose a simple yet effective approach, named Point Adversarial Self Mining (PASM), to improve the recognition accuracy in facial expression recognition.

Adversarial Attack Data Augmentation +2

RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations

no code implementations12 Aug 2020 Wenjing Yan, Shan Li, Chengtao Que, JiQuan Pei, Weihong Deng

Much of the work on automatic facial expression recognition relies on databases containing a certain number of emotion classes and their exaggerated facial configurations (generally six prototypical facial expressions), based on Ekman's Basic Emotion Theory.

Facial Expression Recognition Multi-Label Learning

Omni-supervised Facial Expression Recognition via Distilled Data

no code implementations18 May 2020 Ping Liu, Yunchao Wei, Zibo Meng, Weihong Deng, Joey Tianyi Zhou, Yi Yang

However, the performance of the current state-of-the-art facial expression recognition (FER) approaches is directly related to the labeled data for training.

Facial Expression Recognition

Towards Transferable Adversarial Attack against Deep Face Recognition

no code implementations13 Apr 2020 Yaoyao Zhong, Weihong Deng

In particular, the existence of transferable adversarial examples can severely hinder the robustness of DCNNs since this type of attacks can be applied in a fully black-box manner without queries on the target system.

Adversarial Attack Face Recognition

Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning

no code implementations25 Nov 2019 Mei Wang, Weihong Deng

To encourage fairness, we introduce the idea of adaptive margin to learn balanced performance for different races based on large margin losses.

Face Recognition Fairness +2

Metric Classification Network in Actual Face Recognition Scene

no code implementations25 Oct 2019 Jian Li, Yan Wang, Xiubao Zhang, Weihong Deng, Haifeng Shen

In this paper, we train a validation classifier to normalize the decision threshold, which means that the result can be obtained directly without replacing the threshold.

Classification Face Recognition +2

Adversarial Learning with Margin-based Triplet Embedding Regularization

1 code implementation ICCV 2019 Yaoyao Zhong, Weihong Deng

The Deep neural networks (DNNs) have achieved great success on a variety of computer vision tasks, however, they are highly vulnerable to adversarial attacks.

Classification Face Recognition +1

Mixed High-Order Attention Network for Person Re-Identification

1 code implementation ICCV 2019 Binghui Chen, Weihong Deng, Jiani Hu

Then, rethinking person ReID as a zero-shot learning problem, we propose the Mixed High-Order Attention Network (MHN) to further enhance the discrimination and richness of attention knowledge in an explicit manner.

Person Re-Identification Zero-Shot Learning

Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval

no code implementations CVPR 2019 Binghui Chen, Weihong Deng

In zero-shot image retrieval (ZSIR) task, embedding learning becomes more attractive, however, many methods follow the traditional metric learning idea and omit the problems behind zero-shot settings.

Image Retrieval Metric Learning +1

A Deeper Look at Facial Expression Dataset Bias

no code implementations25 Apr 2019 Shan Li, Weihong Deng

Datasets play an important role in the progress of facial expression recognition algorithms, but they may suffer from obvious biases caused by different cultures and collection conditions.

Facial Expression Recognition

Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

no code implementations CVPR 2019 Tongtong Yuan, Weihong Deng, Jian Tang, Yinan Tang, Binghui Chen

In this paper, different from the approaches on learning the loss structures, we propose a robust SNR distance metric based on Signal-to-Noise Ratio (SNR) for measuring the similarity of image pairs for deep metric learning.

Image Clustering Metric Learning +2

Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering

no code implementations22 Jan 2019 Binghui Chen, Weihong Deng

However, in this paper, we first emphasize that the generalization ability is a core ingredient of this 'good' embedding as well and largely affects the metric performance in zero-shot settings as a matter of fact.

Image Retrieval Metric Learning +1

Virtual Class Enhanced Discriminative Embedding Learning

no code implementations NeurIPS 2018 Binghui Chen, Weihong Deng, Haifeng Shen

Recently, learning discriminative features to improve the recognition performances gradually becomes the primary goal of deep learning, and numerous remarkable works have emerged.

Face Verification General Classification

Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision

no code implementations20 Nov 2018 Wanxin Tian, Zixuan Wang, Haifeng Shen, Weihong Deng, Yiping Meng, Binghui Chen, Xiubao Zhang, Yuan Zhao, Xiehe Huang

We assume that problems inside are inadequate use of supervision information and imbalance between semantics and details at all level feature maps in CNN even with Feature Pyramid Networks (FPN).

Face Detection Semantic Segmentation

ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating

no code implementations4 Jun 2018 Binghui Chen, Weihong Deng

Deep embedding learning becomes more attractive for discriminative feature learning, but many methods still require hard-class mining, which is computationally complex and performance-sensitive.

Image Retrieval

Deep Facial Expression Recognition: A Survey

7 code implementations23 Apr 2018 Shan Li, Weihong Deng

We then introduce the available datasets that are widely used in the literature and provide accepted data selection and evaluation principles for these datasets.

Facial Expression Recognition

Deep Face Recognition: A Survey

6 code implementations18 Apr 2018 Mei Wang, Weihong Deng

Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction.

Face Recognition Face Verification +1

Deep Visual Domain Adaptation: A Survey

no code implementations10 Feb 2018 Mei Wang, Weihong Deng

Deep domain adaption has emerged as a new learning technique to address the lack of massive amounts of labeled data.

Domain Adaptation Face Recognition +4

Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments

no code implementations28 Aug 2017 Tianyue Zheng, Weihong Deng, Jiani Hu

Labeled Faces in the Wild (LFW) database has been widely utilized as the benchmark of unconstrained face verification and due to big data driven machine learning methods, the performance on the database approaches nearly 100%.

Face Recognition Face Verification +1

Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation

no code implementations CVPR 2017 Binghui Chen, Weihong Deng, Junping Du

In this paper, we first emphasize that the early saturation behavior of softmax will impede the exploration of SGD, which sometimes is a reason for model converging at a bad local-minima, then propose Noisy Softmax to mitigating this early saturation issue by injecting annealed noise in softmax during each iteration.

Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild

no code implementations CVPR 2017 Shan Li, Weihong Deng, JunPing Du

Past research on facial expressions have used relatively limited datasets, which makes it unclear whether current methods can be employed in real world.

Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models

no code implementations24 May 2017 Yida Wang, Weihong Deng

In this paper, our generative model trained with synthetic images rendered from 3D models reduces the workload of data collection and limitation of conditions.

Bayesian Inference Metric Learning +2

Multi-Manifold Deep Metric Learning for Image Set Classification

no code implementations CVPR 2015 Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin, Jie zhou

In this paper, we propose a multi-manifold deep metric learning (MMDML) method for image set classification, which aims to recognize an object of interest from a set of image instances captured from varying viewpoints or under varying illuminations.

Classification General Classification +1

Linear Ranking Analysis

no code implementations CVPR 2014 Weihong Deng, Jiani Hu, Jun Guo

We extend the classical linear discriminant analysis (LDA) technique to linear ranking analysis (LRA), by considering the ranking order of classes centroids on the projected subspace.

Zero-Shot Learning

In Defense of Sparsity Based Face Recognition

no code implementations CVPR 2013 Weihong Deng, Jiani Hu, Jun Guo

The success of sparse representation based classification (SRC) has largely boosted the research of sparsity based face recognition in recent years.

Face Recognition Sparse Representation-based Classification

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