5.3k citations · 6.5k across the 44 of their papers we have counts for
44 papers
Img2Vec: A Teacher of High Token-Diversity Helps Masked AutoEncoders
Heng Pan, Chenyang Liu, Wenxiao Wang +4
We present a pipeline of Image to Vector (Img2Vec) for masked image modeling (MIM) with deep features. To study which type of deep features is appropriate for MIM as a learning tar…
Towards In-distribution Compatibility in Out-of-distribution Detection
Boxi Wu, Jie Jiang, Haidong Ren +7
Deep neural network, despite its remarkable capability of discriminating targeted in-distribution samples, shows poor performance on detecting anomalous out-of-distribution data. T…
Hardly Perceptible Trojan Attack against Neural Networks with Bit Flips
Jiawang Bai, Kuofeng Gao, Dihong Gong +3
The security of deep neural networks (DNNs) has attracted increasing attention due to their widespread use in various applications. Recently, the deployed DNNs have been demonstrat…
Versatile Weight Attack via Flipping Limited Bits
Jiawang Bai, Baoyuan Wu, Zhifeng Li +1
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…
Towards Efficient Adversarial Training on Vision Transformers
Boxi Wu, Jindong Gu, Zhifeng Li +3
Vision Transformer (ViT), as a powerful alternative to Convolutional Neural Network (CNN), has received much attention. Recent work showed that ViTs are also vulnerable to adversar…
Tencent Text-Video Retrieval: Hierarchical Cross-Modal Interactions with Multi-Level Representations
Jie Jiang, Shaobo Min, Weijie Kong +4
Text-Video Retrieval plays an important role in multi-modal understanding and has attracted increasing attention in recent years. Most existing methods focus on constructing contra…
Improving Vision Transformers by Revisiting High-frequency Components
Jiawang Bai, Li Yuan, Shu-Tao Xia +3
The transformer models have shown promising effectiveness in dealing with various vision tasks. However, compared with training Convolutional Neural Network (CNN) models, training…
MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees
ZhenZhe Ying, Zhuoer Xu, Zhifeng Li +2
Despite the success of deep learning in computer vision and natural language processing, Gradient Boosted Decision Tree (GBDT) is yet one of the most powerful tools for application…
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…
Learning Spatial Attention for Face Super-Resolution
Chaofeng Chen, Dihong Gong, Hao Wang +2
General image super-resolution techniques have difficulties in recovering detailed face structures when applying to low resolution face images. Recent deep learning based methods t…
Pixel-wise Dense Detector for Image Inpainting
Ruisong Zhang, Weize Quan, Baoyuan Wu +2
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 vi…
Task-agnostic Temporally Consistent Facial Video Editing
Meng Cao, Haozhi Huang, Hao Wang +6
Recent research has witnessed the advances in facial image editing tasks. For video editing, however, previous methods either simply apply transformations frame by frame or utilize…