no code implementations • 15 Jul 2022 • Rui Huang, Ruofei Wang, Qing Guo, Yuxiang Zhang, Wei Fan
Change detection (CD) aims to detect change regions within an image pair captured at different times, playing a significant role for diverse real-world applications.
no code implementations • 25 Apr 2022 • Ruize Han, Wei Feng, Qing Guo, QinGhua Hu
Visual object tracking is an important task in computer vision, which has many real-world applications, e. g., video surveillance, visual navigation.
no code implementations • 24 Mar 2022 • Xiaofei Xie, Tianlin Li, Jian Wang, Lei Ma, Qing Guo, Felix Juefei-Xu, Yang Liu
Inspired by software testing, a number of structural coverage criteria are designed and proposed to measure the test adequacy of DNNs.
1 code implementation • CVPR 2022 • Xiaoguang Li, Qing Guo, Di Lin, Ping Li, Wei Feng, Song Wang
As a result, the final method takes the advantage of effective semantic & image-level filling for high-fidelity inpainting.
no code implementations • 17 Jan 2022 • JiaYi Zhu, Qing Guo, Felix Juefei-Xu, Yihao Huang, Yang Liu, Geguang Pu
Modern face recognition systems (FRS) still fall short when the subjects are wearing facial masks, a common theme in the age of respiratory pandemics.
no code implementations • 16 Jan 2022 • Liangru Sun, Felix Juefei-Xu, Yihao Huang, Qing Guo, JiaYi Zhu, Jincao Feng, Yang Liu, Geguang Pu
To generate unrestricted adversarial examples with high image quality and good transferability, in this paper, we propose Adversarial Lightness Attack (ALA), a white-box unrestricted adversarial attack that focuses on modifying the lightness of the images.
1 code implementation • 7 Jan 2022 • Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Di Lin, Wei Feng, Song Wang
First, we propose the uncertainty-aware cascaded predictive filtering (UC-PFilt) that can identify the difficulties of reconstructing clean pixels via predicted kernels and remove the residual rain traces effectively.
no code implementations • 27 Nov 2021 • Lan Fu, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu, Song Wang
The observation of this work motivates us to design a novel detection-aware shadow removal framework, which empowers shadow removal to achieve higher restoration quality and enhance the shadow robustness of deployed facial landmark detectors.
no code implementations • 26 Nov 2021 • Hua Qi, Zhijie Wang, Qing Guo, Jianlang Chen, Felix Juefei-Xu, Lei Ma, Jianjun Zhao
In this work, as the first attempt, we initiate to repair DNNs by jointly optimizing the architecture and weights at a higher (i. e., block) level.
no code implementations • 25 Nov 2021 • Yihao Huang, Felix Juefei-Xu, Qing Guo, Weikai Miao, Yang Liu, Geguang Pu
Bokeh effect is a natural shallow depth-of-field phenomenon that blurs the out-of-focus part in photography.
no code implementations • 18 Aug 2021 • Ruijun Gao, Qing Guo, Qian Zhang, Felix Juefei-Xu, Hongkai Yu, Wei Feng
To this end, we first propose the physical model-based adversarial relighting attack (ARA) denoted as albedo-quotient-based adversarial relighting attack (AQ-ARA).
no code implementations • 28 Jul 2021 • Qing Guo, Zhijie Wang, Felix Juefei-Xu, Di Lin, Lei Ma, Wei Feng, Yang Liu
3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e. g., high-curvature, concave/convex, and hollowed-out 3D shapes) and the unknown & diverse patterns of the partially available point clouds.
1 code implementation • ICCV 2021 • Qing Guo, Ziyi Cheng, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yang Liu, Jianjun Zhao
In this work, we explore the robustness of visual object trackers against motion blur from a new angle, i. e., adversarial blur attack (ABA).
no code implementations • 14 Jul 2021 • Yihao Huang, Qing Guo, Felix Juefei-Xu, Lei Ma, Weikai Miao, Yang Liu, Geguang Pu
To this end, we first comprehensively investigate two kinds of pixel denoising methods for adversarial robustness enhancement (i. e., existing additive-based and unexplored filtering-based methods) under the loss functions of image-level and semantic-level, respectively, showing that pixel-wise filtering can obtain much higher image quality (e. g., higher PSNR) as well as higher robustness (e. g., higher accuracy on adversarial examples) than existing pixel-wise additive-based method.
1 code implementation • 9 Jul 2021 • Qing Guo, Xiaoguang Li, Felix Juefei-Xu, Hongkai Yu, Yang Liu, Song Wang
In this paper, for the first time, we formulate image inpainting as a mix of two problems, predictive filtering and deep generation.
1 code implementation • 2 Jul 2021 • Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Lawrence Carin, Fan Li, Chenyang Tao
Successful applications of InfoNCE and its variants have popularized the use of contrastive variational mutual information (MI) estimators in machine learning.
1 code implementation • 2 Jul 2021 • Junya Chen, Zhe Gan, Xuan Li, Qing Guo, Liqun Chen, Shuyang Gao, Tagyoung Chung, Yi Xu, Belinda Zeng, Wenlian Lu, Fan Li, Lawrence Carin, Chenyang Tao
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years.
no code implementations • 18 May 2021 • Qing Guo, Felix Juefei-Xu, Changqing Zhou, Yang Liu, Song Wang
In both cases, Sparta leads to CNNs with higher robustness than the vanilla ReLU, verifying the flexibility and versatility of the proposed method.
no code implementations • 12 May 2021 • Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li, Yang Liu
Moreover, we propose the geometry-aware level-set optimization method to solve the adversarial vignetting regions and physical parameters jointly.
no code implementations • 11 May 2021 • Lan Fu, Hongkai Yu, Felix Juefei-Xu, Jinlong Li, Qing Guo, Song Wang
As one of the state-of-the-art perception approaches, detecting the interested objects in each frame of video surveillance is widely desired by ITS.
no code implementations • 28 Apr 2021 • Ruijun Gao, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng
We also visualize the correlation matrices, which inspire us to jointly apply different perturbations to improve the success rate of the attack.
no code implementations • 23 Apr 2021 • Ziyi Cheng, Xuhong Ren, Felix Juefei-Xu, Wanli Xue, Qing Guo, Lei Ma, Jianjun Zhao
Online updating of the object model via samples from historical frames is of great importance for accurate visual object tracking.
1 code implementation • CVPR 2021 • Lan Fu, Changqing Zhou, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu, Song Wang
We conduct extensive experiments on the ISTD, ISTD+, and SRD datasets to validate our method's effectiveness and show better performance in shadow regions and comparable performance in non-shadow regions over the state-of-the-art methods.
1 code implementation • 27 Feb 2021 • Felix Juefei-Xu, Run Wang, Yihao Huang, Qing Guo, Lei Ma, Yang Liu
To fill this gap, in this paper, we provide a comprehensive overview and detailed analysis of the research work on the topic of DeepFake generation, DeepFake detection as well as evasion of DeepFake detection, with more than 318 research papers carefully surveyed.
no code implementations • 1 Jan 2021 • Qing Guo, Felix Juefei-Xu, Changqing Zhou, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu
Moreover, comprehensive evaluations have demonstrated two important properties of our method: First, superior transferability across DNNs.
no code implementations • 19 Nov 2020 • Bing Yu, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jianjun Zhao
In this paper, we propose a style-guided data augmentation for repairing DNN in the operational environment.
no code implementations • 19 Sep 2020 • Binyu Tian, Qing Guo, Felix Juefei-Xu, Wen Le Chan, Yupeng Cheng, Xiaohong Li, Xiaofei Xie, Shengchao Qin
Our method reveals the potential threat to the DNN-based X-ray automated diagnosis and can definitely benefit the development of bias-field-robust automated diagnosis system.
no code implementations • 19 Sep 2020 • Liming Zhai, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Lei Ma, Wei Feng, Shengchao Qin, Yang Liu
To defend the DNNs from the negative rain effect, we also present a defensive deraining strategy, for which we design an adversarial rain augmentation that uses mixed adversarial rain layers to enhance deraining models for downstream DNN perception.
no code implementations • 19 Sep 2020 • Yihao Huang, Felix Juefei-Xu, Qing Guo, Yang Liu, Geguang Pu
We believe that producing DeepFakes that are highly realistic and ``detection evasive'' can serve the ultimate goal of improving future generation DeepFake detection capabilities.
no code implementations • 19 Sep 2020 • Yupeng Cheng, Felix Juefei-Xu, Qing Guo, Huazhu Fu, Xiaofei Xie, Shang-Wei Lin, Weisi Lin, Yang Liu
In this paper, we study this problem from the viewpoint of adversarial attack and identify a totally new task, i. e., adversarial exposure attack generating adversarial images by tuning image exposure to mislead the DNNs with significantly high transferability.
2 code implementations • 19 Sep 2020 • Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu
To fill this gap, in this paper, we regard the single-image deraining as a general image-enhancing problem and originally propose a model-free deraining method, i. e., EfficientDeRain, which is able to process a rainy image within 10~ms (i. e., around 6~ms on average), over 80 times faster than the state-of-the-art method (i. e., RCDNet), while achieving similar de-rain effects.
1 code implementation • CVPR 2022 • Ruijun Gao, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Huazhu Fu, Wei Feng, Yang Liu, Song Wang
In this paper, we address this problem from the perspective of adversarial attacks and identify a novel task: adversarial co-saliency attack.
no code implementations • 14 Jul 2020 • Yupeng Cheng, Qing Guo, Felix Juefei-Xu, Wei Feng, Shang-Wei Lin, Weisi Lin, Yang Liu
To this end, we initiate the very first attempt to study this problem from the perspective of adversarial attack and propose the adversarial denoise attack.
1 code implementation • 13 Jun 2020 • Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu
At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image.
no code implementations • 13 Jun 2020 • Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao
As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors.
1 code implementation • NeurIPS 2020 • Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jian Wang, Bing Yu, Wei Feng, Yang Liu
Besides, the attack is further enhanced by adaptively tuning the translations of object and background.
no code implementations • 27 Jan 2020 • Yihao Huang, Felix Juefei-Xu, Qing Guo, Yang Liu, Geguang Pu
In this work, we investigate the architecture of existing GAN-based face manipulation methods and observe that the imperfection of upsampling methods therewithin could be served as an important asset for GAN-synthesized fake image detection and forgery localization.
no code implementations • 9 Dec 2019 • Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu
In this paper, we investigate and introduce a new type of adversarial attack to evade FR systems by manipulating facial content, called \textbf{\underline{a}dversarial \underline{mor}phing \underline{a}ttack} (a. k. a.
1 code implementation • ECCV 2020 • Qing Guo, Xiaofei Xie, Felix Juefei-Xu, Lei Ma, Zhongguo Li, Wanli Xue, Wei Feng, Yang Liu
We identify that online object tracking poses two new challenges: 1) it is difficult to generate imperceptible perturbations that can transfer across frames, and 2) real-time trackers require the attack to satisfy a certain level of efficiency.
no code implementations • 19 Sep 2019 • Zhu Sun, Qing Guo, Jie Yang, Hui Fang, Guibing Guo, Jie Zhang, Robin Burke
This Research Commentary aims to provide a comprehensive and systematic survey of the recent research on recommender systems with side information.
no code implementations • 21 Aug 2019 • Qing Guo, Wei Feng, Zhihao Chen, Ruijun Gao, Liang Wan, Song Wang
In this paper, we address these two problems by constructing a Blurred Video Tracking benchmark, which contains a variety of videos with different levels of motion blurs, as well as ground truth tracking results for evaluating trackers.
no code implementations • ICCV 2017 • Qing Guo, Wei Feng, Ce Zhou, Rui Huang, Liang Wan, Song Wang
How to effectively learn temporal variation of target appearance, to exclude the interference of cluttered background, while maintaining real-time response, is an essential problem of visual object tracking.
Ranked #5 on
Visual Object Tracking
on OTB-2013