Search Results for author: Zhifeng Li

Found 47 papers, 17 papers with code

Sparse Adversarial Attack via Perturbation Factorization

1 code implementation ECCV 2020 Yanbo Fan, Baoyuan Wu, Tuanhui Li, Yong Zhang, Mingyang Li, Zhifeng Li, Yujiu Yang

Based on this factorization, we formulate the sparse attack problem as a mixed integer programming (MIP) to jointly optimize the binary selection factors and continuous perturbation magnitudes of all pixels, with a cardinality constraint on selection factors to explicitly control the degree of sparsity.

Adversarial Attack

Neural Routing by Memory

no code implementations NeurIPS 2021 Kaipeng Zhang, Zhenqiang Li, Zhifeng Li, Wei Liu, Yoichi Sato

However, they use the same procedure sequence for all inputs, regardless of the intermediate features. This paper proffers a simple yet effective idea of constructing parallel procedures and assigning similar intermediate features to the same specialized procedures in a divide-and-conquer fashion.

Regional Adversarial Training for Better Robust Generalization

no code implementations2 Sep 2021 Chuanbiao Song, Yanbo Fan, Yichen Yang, Baoyuan Wu, Yiming Li, Zhifeng Li, Kun He

Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks.

End2End Occluded Face Recognition by Masking Corrupted Features

no code implementations21 Aug 2021 Haibo Qiu, Dihong Gong, Zhifeng Li, Wei Liu, DaCheng Tao

With the recent advancement of deep convolutional neural networks, significant progress has been made in general face recognition.

Face Recognition

Target Adaptive Context Aggregation for Video Scene Graph Generation

1 code implementation ICCV 2021 Yao Teng, LiMin Wang, Zhifeng Li, Gangshan Wu

Specifically, we design an efficient method for frame-level VidSGG, termed as {\em Target Adaptive Context Aggregation Network} (TRACE), with a focus on capturing spatio-temporal context information for relation recognition.

Graph Generation Scene Graph Generation

SynFace: Face Recognition with Synthetic Data

1 code implementation ICCV 2021 Haibo Qiu, Baosheng Yu, Dihong Gong, Zhifeng Li, Wei Liu, DaCheng Tao

We then analyze the underlying causes behind the performance gap, e. g., the poor intra-class variations and the domain gap between synthetic and real face images.

Face Generation Face Recognition

UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing

no code implementations12 Aug 2021 Meng Cao, HaoZhi Huang, Hao Wang, Xuan Wang, Li Shen, Sheng Wang, Linchao Bao, Zhifeng Li, Jiebo Luo

Compared with the state-of-the-art facial image editing methods, our framework generates video portraits that are more photo-realistic and temporally smooth.

3D Reconstruction Face Reenactment +2

Structure-Regularized Attention for Deformable Object Representation

1 code implementation12 Jun 2021 Shenao Zhang, Li Shen, Zhifeng Li, Wei Liu

Capturing contextual dependencies has proven useful to improve the representational power of deep neural networks.

Attacking Adversarial Attacks as A Defense

no code implementations9 Jun 2021 Boxi Wu, Heng Pan, Li Shen, Jindong Gu, Shuai Zhao, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu

In this work, we find that the adversarial attacks can also be vulnerable to small perturbations.

Image-to-Video Generation via 3D Facial Dynamics

no code implementations31 May 2021 Xiaoguang Tu, Yingtian Zou, Jian Zhao, Wenjie Ai, Jian Dong, Yuan YAO, Zhikang Wang, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.

Video Generation Video Prediction

Joint Face Image Restoration and Frontalization for Recognition

no code implementations12 May 2021 Xiaoguang Tu, Jian Zhao, Qiankun Liu, Wenjie Ai, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

First, MDFR is a well-designed encoder-decoder architecture which extracts feature representation from an input face image with arbitrary low-quality factors and restores it to a high-quality counterpart.

Face Recognition Image Restoration

Backdoor Attack in the Physical World

no code implementations6 Apr 2021 Yiming Li, Tongqing Zhai, Yong Jiang, Zhifeng Li, Shu-Tao Xia

We demonstrate that this attack paradigm is vulnerable when the trigger in testing images is not consistent with the one used for training.

LARNet: Lie Algebra Residual Network for Face Recognition

1 code implementation15 Mar 2021 Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu

We prove that face rotation in the image space is equivalent to an additive residual component in the feature space of CNNs, which is determined solely by the rotation.

Face Recognition Robust Face Recognition

Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits

1 code implementation ICLR 2021 Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia

By utilizing the latest technique in integer programming, we equivalently reformulate this BIP problem as a continuous optimization problem, which can be effectively and efficiently solved using the alternating direction method of multipliers (ADMM) method.

Adversarial Attack

Learning Spatial Attention for Face Super-Resolution

1 code implementation2 Dec 2020 Chaofeng Chen, Dihong Gong, Hao Wang, Zhifeng Li, Kwan-Yee K. Wong

Visualization of the attention maps shows that our spatial attention network can capture the key face structures well even for very low resolution faces (e. g., $16\times16$).

Face Parsing Image Super-Resolution +2

Pixel-wise Dense Detector for Image Inpainting

no code implementations4 Nov 2020 Ruisong Zhang, Weize Quan, Baoyuan Wu, Zhifeng Li, Dong-Ming Yan

Recent GAN-based image inpainting approaches adopt an average strategy to discriminate the generated image and output a scalar, which inevitably lose the position information of visual artifacts.

Image Inpainting

Backdoor Learning: A Survey

1 code implementation17 Jul 2020 Yiming Li, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shu-Tao Xia

Backdoor attack intends to embed hidden backdoor into deep neural networks (DNNs), such that the attacked model performs well on benign samples, whereas its prediction will be maliciously changed if the hidden backdoor is activated by the attacker-defined trigger.

Adversarial Attack Data Poisoning

Task-agnostic Temporally Consistent Facial Video Editing

no code implementations3 Jul 2020 Meng Cao, Hao-Zhi Huang, Hao Wang, Xuan Wang, Li Shen, Sheng Wang, Linchao Bao, Zhifeng Li, Jiebo Luo

Compared with the state-of-the-art facial image editing methods, our framework generates video portraits that are more photo-realistic and temporally smooth.

3D Reconstruction Video Editing

AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks

1 code implementation16 Jun 2020 Yuesong Tian, Li Shen, Guinan Su, Zhifeng Li, Wei Liu

To this end, we propose a fully differentiable search framework for generative adversarial networks, dubbed alphaGAN.

Boosting Black-Box Attack with Partially Transferred Conditional Adversarial Distribution

no code implementations15 Jun 2020 Yan Feng, Baoyuan Wu, Yanbo Fan, Li Liu, Zhifeng Li, Shutao Xia

This work studies black-box adversarial attacks against deep neural networks (DNNs), where the attacker can only access the query feedback returned by the attacked DNN model, while other information such as model parameters or the training datasets are unknown.

Adversarial Attack

Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition

no code implementations25 May 2020 Bing Cao, Nannan Wang, Xinbo Gao, Jie Li, Zhifeng Li

Heterogeneous face recognition (HFR) refers to matching face images acquired from different domains with wide applications in security scenarios.

Face Recognition Heterogeneous Face Recognition +1

Effective and Robust Detection of Adversarial Examples via Benford-Fourier Coefficients

no code implementations12 May 2020 Chengcheng Ma, Baoyuan Wu, Shibiao Xu, Yanbo Fan, Yong Zhang, Xiaopeng Zhang, Zhifeng Li

In this work, we study the detection of adversarial examples, based on the assumption that the output and internal responses of one DNN model for both adversarial and benign examples follow the generalized Gaussian distribution (GGD), but with different parameters (i. e., shape factor, mean, and variance).

Image Classification

Rethinking the Trigger of Backdoor Attack

no code implementations9 Apr 2020 Yiming Li, Tongqing Zhai, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shu-Tao Xia

Backdoor attack intends to inject hidden backdoor into the deep neural networks (DNNs), such that the prediction of the infected model will be maliciously changed if the hidden backdoor is activated by the attacker-defined trigger, while it performs well on benign samples.

Toward Adversarial Robustness via Semi-supervised Robust Training

1 code implementation16 Mar 2020 Yiming Li, Baoyuan Wu, Yan Feng, Yanbo Fan, Yong Jiang, Zhifeng Li, Shu-Tao Xia

In this work, we propose a novel defense method, the robust training (RT), by jointly minimizing two separated risks ($R_{stand}$ and $R_{rob}$), which is with respect to the benign example and its neighborhoods respectively.

Adversarial Defense Adversarial Robustness

Controllable Descendant Face Synthesis

no code implementations26 Feb 2020 Yong Zhang, Le Li, Zhilei Liu, Baoyuan Wu, Yanbo Fan, Zhifeng Li

Most of the existing methods train models for one-versus-one kin relation, which only consider one parent face and one child face by directly using an auto-encoder without any explicit control over the resemblance of the synthesized face to the parent face.

Face Generation

Facial Attribute Capsules for Noise Face Super Resolution

no code implementations16 Feb 2020 Jingwei Xin, Nannan Wang, Xinrui Jiang, Jie Li, Xinbo Gao, Zhifeng Li

In the SR processing, we first generated a group of FACs from the input LR face, and then reconstructed the HR face from this group of FACs.

Image Super-Resolution

Video Face Super-Resolution with Motion-Adaptive Feedback Cell

no code implementations15 Feb 2020 Jingwei Xin, Nannan Wang, Jie Li, Xinbo Gao, Zhifeng Li

Current state-of-the-art CNN methods usually treat the VSR problem as a large number of separate multi-frame super-resolution tasks, at which a batch of low resolution (LR) frames is utilized to generate a single high resolution (HR) frame, and running a slide window to select LR frames over the entire video would obtain a series of HR frames.

Motion Compensation Motion Estimation +2

Squeeze-and-Attention Networks for Semantic Segmentation

1 code implementation CVPR 2020 Zilong Zhong, Zhong Qiu Lin, Rene Bidart, Xiaodan Hu, Ibrahim Ben Daya, Zhifeng Li, Wei-Shi Zheng, Jonathan Li, Alexander Wong

The recent integration of attention mechanisms into segmentation networks improves their representational capabilities through a great emphasis on more informative features.

Ranked #14 on Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)

Semantic Segmentation

Decorrelated Adversarial Learning for Age-Invariant Face Recognition

1 code implementation CVPR 2019 Hao Wang, Dihong Gong, Zhifeng Li, Wei Liu

To reduce such a discrepancy, in this paper we propose a novel algorithm to remove age-related components from features mixed with both identity and age information.

Age-Invariant Face Recognition

Efficient Decision-based Black-box Adversarial Attacks on Face Recognition

no code implementations CVPR 2019 Yinpeng Dong, Hang Su, Baoyuan Wu, Zhifeng Li, Wei Liu, Tong Zhang, Jun Zhu

In this paper, we evaluate the robustness of state-of-the-art face recognition models in the decision-based black-box attack setting, where the attackers have no access to the model parameters and gradients, but can only acquire hard-label predictions by sending queries to the target model.

Face Recognition

Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition

no code implementations ECCV 2018 Yitong Wang, Dihong Gong, Zheng Zhou, Xing Ji, Hao Wang, Zhifeng Li, Wei Liu, Tong Zhang

Extensive experiments conducted on the three public domain face aging datasets (MORPH Album 2, CACD-VS and FG-NET) have shown the effectiveness of the proposed approach and the value of the constructed CAF dataset on AIFR.

Age-Invariant Face Recognition

Detecting Faces Using Inside Cascaded Contextual CNN

no code implementations ICCV 2017 Kaipeng Zhang, Zhanpeng Zhang, Hao Wang, Zhifeng Li, Yu Qiao, Wei Liu

Deep Convolutional Neural Networks (CNNs) achieve substantial improvements in face detection in the wild.

Face Detection

Range Loss for Deep Face Recognition With Long-Tailed Training Data

no code implementations ICCV 2017 Xiao Zhang, Zhiyuan Fang, Yandong Wen, Zhifeng Li, Yu Qiao

Unlike these work, this paper investigated how long-tailed data impact the training of face CNNs and develop a novel loss function, called range loss, to effectively utilize the tailed data in training process.

Face Recognition

Real-Time Neural Style Transfer for Videos

no code implementations CVPR 2017 Hao-Zhi Huang, Hao Wang, Wenhan Luo, Lin Ma, Wenhao Jiang, Xiaolong Zhu, Zhifeng Li, Wei Liu

More specifically, a hybrid loss is proposed to capitalize on the content information of input frames, the style information of a given style image, and the temporal information of consecutive frames.

Style Transfer Video Style Transfer

Face R-CNN

no code implementations4 Jun 2017 Hao Wang, Zhifeng Li, Xing Ji, Yitong Wang

Faster R-CNN is one of the most representative and successful methods for object detection, and has been becoming increasingly popular in various objection detection applications.

Face Detection Object Detection

Range Loss for Deep Face Recognition with Long-tail

2 code implementations28 Nov 2016 Xiao Zhang, Zhiyuan Fang, Yandong Wen, Zhifeng Li, Yu Qiao

Convolutional neural networks have achieved great improvement on face recognition in recent years because of its extraordinary ability in learning discriminative features of people with different identities.

Face Recognition

Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition

no code implementations CVPR 2016 Yandong Wen, Zhifeng Li, Yu Qiao

In order to address this problem, we propose a novel deep face recognition framework to learn the age-invariant deep face features through a carefully designed CNN model.

Age-Invariant Face Recognition

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

38 code implementations11 Apr 2016 Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, Yu Qiao

Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions.

Face Alignment Face Detection

A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition

no code implementations CVPR 2015 Dihong Gong, Zhifeng Li, DaCheng Tao, Jianzhuang Liu, Xuelong. Li

In this paper, we propose a new approach to overcome the representation and matching problems in age invariant face recognition.

Age-Invariant Face Recognition

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