5.3k citations · 6.5k across the 44 of their papers we have counts for
13 papers · 1 filter
Triangle Attack: A Query-efficient Decision-based Adversarial Attack
Xiaosen Wang, Zeliang Zhang, Kangheng Tong +4
Decision-based attack poses a severe threat to real-world applications since it regards the target model as a black box and only accesses the hard prediction label. Great efforts h…
Regional Adversarial Training for Better Robust Generalization
Chuanbiao Song, Yanbo Fan, Yichen Yang +4
Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks. To our knowledge, existing AT-based methods usuall…
Target Adaptive Context Aggregation for Video Scene Graph Generation
Yao Teng, Limin Wang, Zhifeng Li +1
This paper deals with a challenging task of video scene graph generation (VidSGG), which could serve as a structured video representation for high-level understanding tasks. We pre…
UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing
Meng Cao, Haozhi Huang, Hao Wang +6
Recent research has witnessed advances in facial image editing tasks including face swapping and face reenactment. However, these methods are confined to dealing with one specific…
End2End Occluded Face Recognition by Masking Corrupted Features
Haibo Qiu, Dihong Gong, Zhifeng Li +2
With the recent advancement of deep convolutional neural networks, significant progress has been made in general face recognition. However, the state-of-the-art general face recogn…
SynFace: Face Recognition with Synthetic Data
Haibo Qiu, Baosheng Yu, Dihong Gong +3
With the recent success of deep neural networks, remarkable progress has been achieved on face recognition. However, collecting large-scale real-world training data for face recogn…
Structure-Regularized Attention for Deformable Object Representation
Shenao Zhang, Li Shen, Zhifeng Li +1
Capturing contextual dependencies has proven useful to improve the representational power of deep neural networks. Recent approaches that focus on modeling global context, such as…
Attacking Adversarial Attacks as A Defense
Boxi Wu, Heng Pan, Li Shen +6
It is well known that adversarial attacks can fool deep neural networks with imperceptible perturbations. Although adversarial training significantly improves model robustness, fai…
Image-to-Video Generation via 3D Facial Dynamics
Xiaoguang Tu, Yingtian Zou, Jian Zhao +8
We present a versatile model, FaceAnime, for various video generation tasks from still images. Video generation from a single face image is an interesting problem and usually tackl…
Joint Face Image Restoration and Frontalization for Recognition
Xiaoguang Tu, Jian Zhao, Qiankun Liu +5
In real-world scenarios, many factors may harm face recognition performance, e.g., large pose, bad illumination,low resolution, blur and noise. To address these challenges, previou…
Backdoor Attack in the Physical World
Yiming Li, Tongqing Zhai, Yong Jiang +2
Backdoor attack intends to inject hidden backdoor into the deep neural networks (DNNs), such that the prediction of infected models will be maliciously changed if the hidden backdo…
LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong +3
Face recognition is an important yet challenging problem in computer vision. A major challenge in practical face recognition applications lies in significant variations between pro…
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits
Jiawang Bai, Baoyuan Wu, Yong Zhang +3
To explore the vulnerability of deep neural networks (DNNs), many attack paradigms have been well studied, such as the poisoning-based backdoor attack in the training stage and the…