2 code implementations • 3 Mar 2024 • Shangquan Sun, Wenqi Ren, Jingzhi Li, Rui Wang, Xiaochun Cao
Knowledge distillation involves transferring soft labels from a teacher to a student using a shared temperature-based softmax function.
Ranked #1 on Knowledge Distillation on CIFAR-100
2 code implementations • 14 Nov 2023 • Peng Jin, Ryuichi Takanobu, Wancai Zhang, Xiaochun Cao, Li Yuan
Large language models have demonstrated impressive universal capabilities across a wide range of open-ended tasks and have extended their utility to encompass multimodal conversations.
Image-based Generative Performance Benchmarking Language Modelling +9
1 code implementation • 5 Nov 2022 • Tao Wang, Kaihao Zhang, Xuanxi Chen, Wenhan Luo, Jiankang Deng, Tong Lu, Xiaochun Cao, Wei Liu, Hongdong Li, Stefanos Zafeiriou
Second, we discuss the challenges of face restoration.
2 code implementations • 6 Feb 2024 • Yichen Shi, Yuhao Gao, Yingxin Lai, Hongyang Wang, Jun Feng, Lei He, Jun Wan, Changsheng chen, Zitong Yu, Xiaochun Cao
For the face forgery detection task, we evaluate GAN-based and diffusion-based data with both visual and acoustic modalities.
2 code implementations • ECCV 2020 • Ben Niu, Weilei Wen, Wenqi Ren, Xiangde Zhang, Lianping Yang, Shuzhen Wang, Kaihao Zhang, Xiaochun Cao, Haifeng Shen
Informative features play a crucial role in the single image super-resolution task.
Ranked #2 on Image Super-Resolution on Urban100 - 8x upscaling
3 code implementations • 19 May 2018 • Huazhu Fu, Jun Cheng, Yanwu Xu, Changqing Zhang, Damon Wing Kee Wong, Jiang Liu, Xiaochun Cao
Specifically, a novel Disc-aware Ensemble Network (DENet) for automatic glaucoma screening is proposed, which integrates the deep hierarchical context of the global fundus image and the local optic disc region.
3 code implementations • 3 Jan 2018 • Huazhu Fu, Jun Cheng, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, Xiaochun Cao
The proposed M-Net mainly consists of multi-scale input layer, U-shape convolutional network, side-output layer, and multi-label loss function.
Ranked #4 on Optic Disc Segmentation on REFUGE
1 code implementation • CVPR 2019 • Siyuan Li, Iago Breno Araujo, Wenqi Ren, Zhangyang Wang, Eric K. Tokuda, Roberto Hirata Junior, Roberto Cesar-Junior, Jiawan Zhang, Xiaojie Guo, Xiaochun Cao
We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images. This dataset highlights diverse data sources and image contents, and is divided into three subsets (rain streak, rain drop, rain and mist), each serving different training or evaluation purposes.
1 code implementation • TPAMI 2022 • Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
The critical challenge along this course lies in the difficulty of performing gradient-based optimization with end-to-end stochastic training, even with a proper choice of surrogate loss.
2 code implementations • TPAMI 2023 • Zhiyong Yang, Qianqian Xu, Wenzheng Hou, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
On top of this, we can show that: 1) Under mild conditions, AdAUC can be optimized equivalently with score-based or instance-wise-loss-based perturbations, which is compatible with most of the popular adversarial example generation methods.
1 code implementation • CVPR 2019 • Xiaojun Jia, Xingxing Wei, Xiaochun Cao, Hassan Foroosh
In other words, ComDefend can transform the adversarial image to its clean version, which is then fed to the trained classifier.
1 code implementation • CVPR 2022 • Xiaojun Jia, Yong Zhang, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao
In this paper, we propose a novel framework for adversarial training by introducing the concept of "learnable attack strategy", dubbed LAS-AT, which learns to automatically produce attack strategies to improve the model robustness.
2 code implementations • 30 Nov 2018 • Xingxing Wei, Siyuan Liang, Ning Chen, Xiaochun Cao
Adversarial examples have been demonstrated to threaten many computer vision tasks including object detection.
1 code implementation • Conference 2023 • Yuning Cui, Yi Tao, Zhenshan Bing, Wenqi Ren, Xinwei Gao, Xiaochun Cao, Kai Huang, Alois Knoll
Image restoration aims to reconstruct the latent sharp image from its corrupted counterpart.
Ranked #1 on Deblurring on RSBlur
1 code implementation • CVPR 2021 • Zhuoran Zheng, Wenqi Ren, Xiaochun Cao, Xiaobin Hu, Tao Wang, Fenglong Song, Xiuyi Jia
To address the problem, we propose a novel network capable of real-time dehazing of 4K images on a single GPU, which consists of three deep CNNs.
2 code implementations • 1 Aug 2021 • Xiaojun Jia, Huanqian Yan, Yonglin Wu, Xingxing Wei, Xiaochun Cao, Yong Zhang
Moreover, we have applied the proposed methods to competition ACM MM2021 Robust Logo Detection that is organized by Alibaba on the Tianchi platform and won top 2 in 36489 teams.
1 code implementation • ICCV 2023 • Aiping Zhang, Wenqi Ren, Yi Liu, Xiaochun Cao
Our method employs superpixels to cluster local similar pixels to form the explicable local regions and utilizes intra-superpixel attention to enable local information interaction.
1 code implementation • 25 Dec 2023 • Xiaoxu Chen, Jingfan Tan, Tao Wang, Kaihao Zhang, Wenhan Luo, Xiaochun Cao
We propose BFRffusion which is thoughtfully designed to effectively extract features from low-quality face images and could restore realistic and faithful facial details with the generative prior of the pretrained Stable Diffusion.
1 code implementation • 14 Feb 2024 • Ruoyu Chen, Hua Zhang, Siyuan Liang, Jingzhi Li, Xiaochun Cao
For incorrectly predicted samples, our method achieves gains of 81. 0% and 18. 4% compared to the HSIC-Attribution algorithm in the average highest confidence and Insertion score respectively.
1 code implementation • ICCV 2023 • Yuning Cui, Wenqi Ren, Xiaochun Cao, Alois Knoll
Image restoration aims to reconstruct a sharp image from its degraded counterpart, which plays an important role in many fields.
Ranked #7 on Image Dehazing on SOTS Outdoor
1 code implementation • NIPS 2022 • Shangquan Sun, Wenqi Ren, Tao Wang, Xiaochun Cao
To address the issue, we propose a targeted adversarial attack in the restoration procedure to boost object detection performance after restoration.
1 code implementation • ECCV 2020 • Xiaobin Hu, Wenqi Ren, John LaMaster, Xiaochun Cao, Xiaoming Li, Zechao Li, Bjoern Menze, Wei Liu
State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local appearance knowledge.
1 code implementation • 26 Oct 2023 • Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqain Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr
This survey explores the landscape of the adversarial transferability of adversarial examples.
1 code implementation • 17 Jul 2022 • Xinwei Liu, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia, Xiaochun Cao
Inspired by the vulnerability of DNNs on adversarial perturbations, we propose a novel defence mechanism by adversarial machine learning for good.
1 code implementation • ICML Workshop AML 2021 • Yiming Li, Linghui Zhu, Xiaojun Jia, Yong Jiang, Shu-Tao Xia, Xiaochun Cao
In this paper, we explore the defense from another angle by verifying whether a suspicious model contains the knowledge of defender-specified \emph{external features}.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2023 • Yuning Cui, Wenqi Ren, Xiaochun Cao, Alois Knoll
Image restoration aims to reconstruct the latent sharp image from its corrupted counterpart.
Ranked #2 on Image Dehazing on SOTS Outdoor
1 code implementation • 27 Mar 2021 • Shuren Qi, Yushu Zhang, Chao Wang, Jiantao Zhou, Xiaochun Cao
Image representation is an important topic in computer vision and pattern recognition.
3 code implementations • 26 Nov 2020 • Qijian Zhang, Runmin Cong, Chongyi Li, Ming-Ming Cheng, Yuming Fang, Xiaochun Cao, Yao Zhao, Sam Kwong
Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains an open and challenging problem.
1 code implementation • 24 Jun 2022 • Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
Knowledge graph (KG) embeddings have shown great power in learning representations of entities and relations for link prediction tasks.
1 code implementation • ICML 2023 • Yuning Cui, Wenqi Ren, Sining Yang, Xiaochun Cao, Alois Knoll
We present IRNeXt, a simple yet effective convolutional network architecture for image restoration.
Ranked #4 on Image Dehazing on SOTS Outdoor
1 code implementation • 18 Jul 2022 • Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao
Based on the observation, we propose a prior-guided FGSM initialization method to avoid overfitting after investigating several initialization strategies, improving the quality of the AEs during the whole training process.
Adversarial Attack Adversarial Attack on Video Classification
1 code implementation • 8 Mar 2024 • Tianrui Lou, Xiaojun Jia, Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, Xiaochun Cao
We find that concealing deformation perturbations in areas insensitive to human eyes can achieve a better trade-off between imperceptibility and adversarial strength, specifically in parts of the object surface that are complex and exhibit drastic curvature changes.
1 code implementation • ACM Transactions on Multimedia Computing, Communications and Applications 2022 • Ruoyu Chen, Jingzhi Li, Hua Zhang, Changchong Sheng, Li Liu, Xiaochun Cao
Different from existing models, in this paper, we propose a new interpretation method that explains the image similarity models by salience maps and attribute words.
1 code implementation • 7 Mar 2024 • Qilang Ye, Zitong Yu, Rui Shao, Xinyu Xie, Philip Torr, Xiaochun Cao
This paper focuses on the challenge of answering questions in scenarios that are composed of rich and complex dynamic audio-visual components.
Audio-visual Question Answering Audio-Visual Question Answering (AVQA) +5
1 code implementation • ICCV 2021 • Senyou Deng, Wenqi Ren, Yanyang Yan, Tao Wang, Fenglong Song, Xiaochun Cao
Although recent research has witnessed a significant progress on the video deblurring task, these methods struggle to reconcile inference efficiency and visual quality simultaneously, especially on ultra-high-definition (UHD) videos (e. g., 4K resolution).
1 code implementation • 7 May 2023 • Yuhan Chen, Yihong Luo, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao
Motivated by it, we propose to use the local similarity (LocalSim) to learn node-level weighted fusion, which can also serve as a plug-and-play module.
1 code implementation • ICML 2021 • Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
The critical challenge along this course lies in the difficulty of performing gradient-based optimization with end-to-end stochastic training, even with a proper choice of surrogate loss.
1 code implementation • 17 Nov 2017 • Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan YAO
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years.
1 code implementation • NeurIPS 2019 • Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
Instead of transforming all the samples into a joint modality-independent space, our framework learns the mappings across individual modal spaces by virtue of cycle-consistency.
1 code implementation • 22 Oct 2022 • Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
In this paper, a systematic analysis reveals that most existing metrics are essentially inconsistent with the aforementioned goal of OSR: (1) For metrics extended from close-set classification, such as Open-set F-score, Youden's index, and Normalized Accuracy, a poor open-set prediction can escape from a low performance score with a superior close-set prediction.
1 code implementation • 2 Feb 2024 • Dingcheng Yang, Yang Bai, Xiaojun Jia, Yang Liu, Xiaochun Cao, Wenjian Yu
The MMP-Attack shows a notable advantage over existing works with superior universality and transferability, which can effectively attack commercial text-to-image (T2I) models such as DALL-E 3.
1 code implementation • 24 Oct 2023 • Xiaojun Jia, Jianshu Li, Jindong Gu, Yang Bai, Xiaochun Cao
Besides, we provide theoretical analysis to show the model robustness can be improved by the single-step adversarial training with sampled subnetworks.
1 code implementation • 18 Feb 2024 • Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao
However, this paper introduces a novel and previously unrecognized threat in face forgery detection scenarios caused by backdoor attack.
1 code implementation • ACM MM 2021 2021 • Zitai Wang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
As the core of the framework, the iterative relabeling module exploits the self-training principle to dynamically generate pseudo labels for user preferences.
1 code implementation • NeurIPS 2019 • Zhiyong Yang, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang
Different from most of the previous work, pursuing the Block-Diagonal structure of LTAM (assigning latent tasks to output tasks) alleviates negative transfer via collaboratively grouping latent tasks and output tasks such that inter-group knowledge transfer and sharing is suppressed.
1 code implementation • 5 Dec 2018 • Ke Ma, Qianqian Xu, Zhiyong Yang, Xiaochun Cao
To address the issue of insufficient training samples, we propose a margin distribution learning paradigm for ordinal embedding, entitled Distributional Margin based Ordinal Embedding (\textit{DMOE}).
1 code implementation • 2 Mar 2022 • Shuren Qi, Yushu Zhang, Chao Wang, Jiantao Zhou, Xiaochun Cao
Image forensics is a rising topic as the trustworthy multimedia content is critical for modern society.
1 code implementation • 13 Sep 2022 • Ke Ma, Qianqian Xu, Jinshan Zeng, Guorong Li, Xiaochun Cao, Qingming Huang
From the perspective of the dynamical system, the attack behavior with a target ranking list is a fixed point belonging to the composition of the adversary and the victim.
1 code implementation • 7 Oct 2023 • Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
However, existing generalization analysis of such losses is still coarse-grained and fragmented, failing to explain some empirical results.
Ranked #6 on Long-tail Learning on CIFAR-10-LT (ρ=10)
1 code implementation • NeurIPS 2023 • Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
However, existing generalization analysis of such losses is still coarse-grained and fragmented, failing to explain some empirical results.
1 code implementation • 4 Aug 2022 • Yiming Li, Linghui Zhu, Xiaojun Jia, Yang Bai, Yong Jiang, Shu-Tao Xia, Xiaochun Cao
In general, we conduct the ownership verification by verifying whether a suspicious model contains the knowledge of defender-specified external features.
1 code implementation • NeurIPS 2023 • Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Collaborative Metric Learning (CML) has recently emerged as a popular method in recommendation systems (RS), closing the gap between metric learning and Collaborative Filtering.
1 code implementation • 18 Jan 2023 • Shuren Qi, Yushu Zhang, Chao Wang, Tao Xiang, Xiaochun Cao, Yong Xiang
In this paper, we explore a non-learning paradigm that aims to derive robust representation directly from noisy images, without the denoising as pre-processing.
1 code implementation • ACM MM 2019 • Shilong Bao, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao, Qingming Huang
From the margin theory point-of-view, we then propose a generalization enhancement scheme for sparse and insufficient labels via optimizing the margin distribution.
1 code implementation • 5 Dec 2018 • Ke Ma, Qianqian Xu, Xiaochun Cao
Existing ordinal embedding methods usually follow a two-stage routine: outlier detection is first employed to pick out the inconsistent comparisons; then an embedding is learned from the clean data.
1 code implementation • 5 Jul 2021 • Ke Ma, Qianqian Xu, Jinshan Zeng, Xiaochun Cao, Qingming Huang
In this paper, to the best of our knowledge, we initiate the first systematic investigation of data poisoning attacks on pairwise ranking algorithms, which can be formalized as the dynamic and static games between the ranker and the attacker and can be modeled as certain kinds of integer programming problems.
1 code implementation • 20 Sep 2022 • Jiawei Liang, Siyuan Liang, Aishan Liu, Ke Ma, Jingzhi Li, Xiaochun Cao
Specifically, we propose a sample-specific data augmentation to transfer the teacher model's ability in capturing distinct frequency components and suggest an adversarial feature augmentation to extract the teacher model's perceptions of non-robust features in the data.
2 code implementations • Proceedings of the 30th ACM International Conference on Multimedia 2022 • Junyu Chen, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
We develop a multi-class AUC optimization work to deal with the class imbalance problem.
1 code implementation • NeurIPS 2019 • Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan YAO
In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective.
1 code implementation • 3 Sep 2022 • Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang
Finally, the experimental results on four benchmark datasets validate the effectiveness of our proposed framework.
1 code implementation • TPAMI 2023 • Zhiyong Yang, Qianqian Xu, Shilong Bao, Peisong Wen, Xiaochun Cao, Qingming Huang
We propose a new result that not only addresses the interdependency issue but also brings a much sharper bound with weaker assumptions about the loss function.
1 code implementation • 23 Feb 2024 • Shuren Qi, Yushu Zhang, Chao Wang, Zhihua Xia, Xiaochun Cao, Jian Weng
Developing robust and interpretable vision systems is a crucial step towards trustworthy artificial intelligence.
1 code implementation • NeurIPS 2023 • Siran Dai, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
To tackle this challenge, methodically we propose an instance-wise surrogate loss of Distributionally Robust AUC (DRAUC) and build our optimization framework on top of it.
1 code implementation • 24 Mar 2024 • Siyuan Liang, Wei Wang, Ruoyu Chen, Aishan Liu, Boxi Wu, Ee-Chien Chang, Xiaochun Cao, DaCheng Tao
This paper aims to bridge this gap by conducting a comprehensive review and analysis of object detectors in open environments.
no code implementations • CVPR 2018 • Wenqi Ren, Lin Ma, Jiawei Zhang, Jinshan Pan, Xiaochun Cao, Wei Liu, Ming-Hsuan Yang
The proposed algorithm hinges on an end-to-end trainable neural network that consists of an encoder and a decoder.
Ranked #23 on Image Dehazing on SOTS Outdoor
no code implementations • 8 Mar 2018 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan YAO
In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or social utility function which generates their comparison behaviors in experiments.
no code implementations • 18 Nov 2017 • Zhiyong Yang, Qianqian Xu, Xiaochun Cao, Qingming Huang
However, both categories ignore the joint effect of the two mentioned factors: the personal diversity with respect to the global consensus; and the intrinsic correlation among multiple attributes.
no code implementations • 4 Nov 2017 • Runmin Cong, Jianjun Lei, Huazhu Fu, Weisi Lin, Qingming Huang, Xiaochun Cao, Chunping Hou
In this paper, we propose an iterative RGBD co-saliency framework, which utilizes the existing single saliency maps as the initialization, and generates the final RGBD cosaliency map by using a refinement-cycle model.
no code implementations • 14 Oct 2017 • Runmin Cong, Jianjun Lei, Changqing Zhang, Qingming Huang, Xiaochun Cao, Chunping Hou
Stereoscopic perception is an important part of human visual system that allows the brain to perceive depth.
no code implementations • 14 Oct 2017 • Runmin Cong, Jianjun Lei, Huazhu Fu, Qingming Huang, Xiaochun Cao, Chunping Hou
Different from the most existing co-saliency methods focusing on RGB images, this paper proposes a novel co-saliency detection model for RGBD images, which utilizes the depth information to enhance identification of co-saliency.
no code implementations • 28 Feb 2017 • Long Chen, Junyu Dong, Shengke Wang, Kin-Man Lam, Muwei Jian, Hua Zhang, Xiaochun Cao
To bridge this gap, we introduce a cascaded structure to eliminate background and exploit a one-vs-rest loss to capture more minute variances among different subordinate categories.
no code implementations • ICCV 2017 • Wenqi Ren, Jinshan Pan, Xiaochun Cao, Ming-Hsuan Yang
We analyze the relationship between motion blur trajectory and optical flow, and present a novel pixel-wise non-linear kernel model to account for motion blur.
no code implementations • 12 Jul 2016 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan YAO
In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or utility function which generates their comparison behaviors in experiments.
no code implementations • 6 Jul 2016 • Le Dong, Ling He, Gaipeng Kong, Qianni Zhang, Xiaochun Cao, Ebroul Izquierdo
In this paper, we propose a compact network called CUNet (compact unsupervised network) to counter the image classification challenge.
no code implementations • 3 Jul 2016 • Le Dong, Zhiyu Lin, Yan Liang, Ling He, Ning Zhang, Qi Chen, Xiaochun Cao, Ebroul lzquierdo
The proposed ICP framework consists of two mechanisms, i. e. SICP (Static ICP) and DICP (Dynamic ICP).
no code implementations • 19 May 2016 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan YAO
With the rapid growth of crowdsourcing platforms it has become easy and relatively inexpensive to collect a dataset labeled by multiple annotators in a short time.
no code implementations • 25 Apr 2016 • Si Liu, Xinyu Ou, Ruihe Qian, Wei Wang, Xiaochun Cao
In this paper, we propose a novel Deep Localized Makeup Transfer Network to automatically recommend the most suitable makeup for a female and synthesis the makeup on her face.
no code implementations • 25 Mar 2016 • Yan Yan, Hanzi Wang, Si Chen, Xiaochun Cao, David Zhang
This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes.
no code implementations • CVPR 2015 • Si Liu, Xiaodan Liang, Luoqi Liu, Xiaohui Shen, Jianchao Yang, Changsheng Xu, Liang Lin, Xiaochun Cao, Shuicheng Yan
Under the classic K Nearest Neighbor (KNN)-based nonparametric framework, the parametric Matching Convolutional Neural Network (M-CNN) is proposed to predict the matching confidence and displacements of the best matched region in the testing image for a particular semantic region in one KNN image.
no code implementations • 15 Aug 2014 • Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan YAO
In this paper we study the problem of how to estimate such visual properties from a ranking perspective with the help of the annotators from online crowdsourcing platforms.
no code implementations • 29 Jul 2018 • Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan YAO
A preference order or ranking aggregated from pairwise comparison data is commonly understood as a strict total order.
no code implementations • 16 Nov 2018 • Runmin Cong, Jianjun Lei, Huazhu Fu, Qingming Huang, Xiaochun Cao, Nam Ling
In this paper, we propose a novel co-saliency detection method for RGBD images based on hierarchical sparsity reconstruction and energy function refinement.
no code implementations • NeurIPS 2018 • Wenqi Ren, Jiawei Zhang, Lin Ma, Jinshan Pan, Xiaochun Cao, WangMeng Zuo, Wei Liu, Ming-Hsuan Yang
In this paper, we present a deep convolutional neural network to capture the inherent properties of image degradation, which can handle different kernels and saturated pixels in a unified framework.
no code implementations • CVPR 2013 • Xiaojie Guo, Xiaochun Cao, Xiaowu Chen, Yi Ma
Given an area of interest in a video sequence, one may want to manipulate or edit the area, e. g. remove occlusions from or replace with an advertisement on it.
no code implementations • CVPR 2014 • Xiaojie Guo, Xiaochun Cao, Yi Ma
When one records a video/image sequence through a transparent medium (e. g. glass), the image is often a superposition of a transmitted layer (scene behind the medium) and a reflected layer.
no code implementations • CVPR 2014 • Xiaowu Chen, Dongqing Zou, Jianwei Li, Xiaochun Cao, Qinping Zhao, Hao Zhang
Previous approaches for edit propagation typically employ a global optimization over the whole set of image pixels, incurring a prohibitively high memory and time consumption for high-resolution images.
no code implementations • CVPR 2015 • Xiaochun Cao, Changqing Zhang, Huazhu Fu, Si Liu, Hua Zhang
In this paper, we focus on how to boost the multi-view clustering by exploring the complementary information among multi-view features.
no code implementations • CVPR 2016 • Hua Zhang, Si Liu, Changqing Zhang, Wenqi Ren, Rui Wang, Xiaochun Cao
In this study, we present a weakly supervised approach that discovers the discriminative structures of sketch images, given pairs of sketch images and web images.
no code implementations • CVPR 2016 • Si Liu, Tianzhu Zhang, Xiaochun Cao, Changsheng Xu
In this paper, we propose a novel structural correlation filter (SCF) model for robust visual tracking.
no code implementations • CVPR 2017 • Wei Zhang, Xiaochun Cao, Rui Wang, Yuanfang Guo, Zhineng Chen
Second, we further extend bMS to a more general form, namely contrastive binary mean shift (cbMS), which maximizes the contrastive density in binary space, for finding informative patterns that are both frequent and discriminative for the dataset.
no code implementations • CVPR 2017 • Yanyang Yan, Wenqi Ren, Yuanfang Guo, Rui Wang, Xiaochun Cao
The proposed method takes advantage of both Bright and Dark Channel Prior.
no code implementations • CVPR 2017 • Changqing Zhang, QinGhua Hu, Huazhu Fu, Pengfei Zhu, Xiaochun Cao
In this paper, we propose a novel Latent Multi-view Subspace Clustering (LMSC) method, which clusters data points with latent representation and simultaneously explores underlying complementary information from multiple views.
no code implementations • ICCV 2015 • Changqing Zhang, Huazhu Fu, Si Liu, Guangcan Liu, Xiaochun Cao
We introduce a low-rank tensor constraint to explore the complementary information from multiple views and, accordingly, establish a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC).
no code implementations • CVPR 2019 • Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, Yuan YAO
The problem of estimating subjective visual properties (SVP) of images (e. g., Shoes A is more comfortable than B) is gaining rising attention.
no code implementations • 18 Jun 2019 • Zhiyong Yang, Qianqian Xu, Xiaochun Cao, Qingming Huang
Traditionally, most of the existing attribute learning methods are trained based on the consensus of annotations aggregated from a limited number of annotators.
no code implementations • 9 Jan 2018 • Yuanfang Guo, Xiaochun Cao, Wei zhang, Rui Wang
Based on our observations, i. e., potential traces in the hue, saturation, dark and bright channels, we propose two simple yet effective detection methods for fake colorized images: Histogram based Fake Colorized Image Detection (FCID-HIST) and Feature Encoding based Fake Colorized Image Detection (FCID-FE).
Multimedia
no code implementations • 11 Sep 2019 • Xiaojun Jia, Xingxing Wei, Xiaochun Cao
We propose the temporal defense, which reconstructs the polluted frames with their temporally neighbor clean frames, to deal with the adversarial videos with sparse polluted frames.
no code implementations • 1 Dec 2019 • Ke Ma, Jinshan Zeng, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan YAO
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years.
no code implementations • 29 Apr 2020 • Zhiyong Yang, Qianqian Xu, Xiaochun Cao, Qingming Huang
To this end, we propose a novel multi-task learning method called Task-Feature Collaborative Learning (TFCL).
no code implementations • ECCV 2020 • Siyuan Liang, Xingxing Wei, Siyuan Yao, Xiaochun Cao
In this paper, we analyze the weakness of object trackers based on the Siamese network and then extend adversarial examples to visual object tracking.
no code implementations • 12 Nov 2020 • Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes.
no code implementations • 11 Apr 2021 • Binyi Su, Zhong Zhou, Haiyong Chen, Xiaochun Cao
Moreover, we release a new solar cell EL image dataset named as EL-2019, which includes three types of images: crack, finger interruption and defect-free.
no code implementations • CVPR 2021 • Pengwen Dai, Sanyi Zhang, Hua Zhang, Xiaochun Cao
In the second stage, the contours of the oriented text proposals are iteratively regressed to arbitrarily shaped ones.
no code implementations • 25 Jul 2021 • Pengwen Dai, Xiaochun Cao
In this paper, we carefully examine and analyze the inconsistent settings, and propose a unified framework for the bottom-up based scene text detection methods.
no code implementations • TPAMI 2021 • Zhiyong Yang, Qianqian Xu, Shilong Bao, Xiaochun Cao, Qingming Huang
Our foundation is based on the M metric, which is a well-known multiclass extension of AUC.
no code implementations • ICCV 2021 • Xiaobin Hu, Wenqi Ren, Kaicheng Yu, Kaihao Zhang, Xiaochun Cao, Wei Liu, Bjoern Menze
Multi-scale and multi-patch deep models have been shown effective in removing blurs of dynamic scenes.
no code implementations • ICCV 2021 • Zhuoran Zheng, Wenqi Ren, Xiaochun Cao, Tao Wang, Xiuyi Jia
First, we propose a dual-path network to extract content and chromatic features at a reduced resolution of the low dynamic range (LDR) input.
no code implementations • 11 Oct 2021 • Xiaojun Jia, Yong Zhang, Baoyuan Wu, Jue Wang, Xiaochun Cao
Adversarial training (AT) has been demonstrated to be effective in improving model robustness by leveraging adversarial examples for training.
no code implementations • NeurIPS 2021 • Liang Yang, Mengzhe Li, Liyang Liu, bingxin niu, Chuan Wang, Xiaochun Cao, Yuanfang Guo
Based on this attribute homophily rate, we propose a Diverse Message Passing (DMP) framework, which specifies every attribute propagation weight on each edge.
no code implementations • ICML Workshop AML 2021 • Siyuan Liang, Xingxing Wei, Xiaochun Cao
The existing attack methods have the following problems: 1) the training generator takes a long time and is difficult to extend to a large dataset; 2) the excessive destruction of the image features does not improve the black-box attack effect(the generated adversarial examples have poor transferability) and brings about visible perturbations.
no code implementations • ICCV 2021 • Siyuan Liang, Baoyuan Wu, Yanbo Fan, Xingxing Wei, Xiaochun Cao
Extensive experiments demonstrate that our method can effectively and efficiently attack various popular object detectors, including anchor-based and anchor-free, and generate transferable adversarial examples.
no code implementations • 23 Apr 2022 • Yushu Zhang, Nuo Chen, Shuren Qi, Mingfu Xue, Xiaochun Cao
In this paper, we try to explore a solution from the perspective of the spatial correlation, which exhibits the generic detection capability for both conventional and deep learning-based recoloring.
no code implementations • 21 May 2022 • Zechen Liang, Yuan-Gen Wang, Wei Lu, Xiaochun Cao
Semi-Supervised Learning (SSL) has advanced classification tasks by inputting both labeled and unlabeled data to train a model jointly.
no code implementations • 17 Jun 2022 • Xiao Dong, Xunlin Zhan, Yunchao Wei, XiaoYong Wei, YaoWei Wang, Minlong Lu, Xiaochun Cao, Xiaodan Liang
Our goal in this research is to study a more realistic environment in which we can conduct weakly-supervised multi-modal instance-level product retrieval for fine-grained product categories.
no code implementations • TPAMI 2022 • Shilong Bao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
However, in this work, by taking a theoretical analysis, we find that negative sampling would lead to a biased estimation of the generalization error.
no code implementations • 14 Jul 2022 • Sanyi Zhang, Xiaochun Cao, Guo-Jun Qi, Zhanjie Song, Jie zhou
Most state-of-the-art instance-level human parsing models adopt two-stage anchor-based detectors and, therefore, cannot avoid the heuristic anchor box design and the lack of analysis on a pixel level.
no code implementations • 16 Sep 2022 • Siyuan Liang, Longkang Li, Yanbo Fan, Xiaojun Jia, Jingzhi Li, Baoyuan Wu, Xiaochun Cao
Recent studies have shown that detectors based on deep models are vulnerable to adversarial examples, even in the black-box scenario where the attacker cannot access the model information.
no code implementations • 26 Sep 2022 • Yangbangyan Jiang, Xiaodan Li, Yuefeng Chen, Yuan He, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang
In recent years, great progress has been made to incorporate unlabeled data to overcome the inefficiently supervised problem via semi-supervised learning (SSL).
3 code implementations • 6 Oct 2022 • Runmin Cong, Qinwei Lin, Chen Zhang, Chongyi Li, Xiaochun Cao, Qingming Huang, Yao Zhao
Focusing on the issue of how to effectively capture and utilize cross-modality information in RGB-D salient object detection (SOD) task, we present a convolutional neural network (CNN) model, named CIR-Net, based on the novel cross-modality interaction and refinement.
no code implementations • 1 Apr 2023 • Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao
This initialization is generated by using high-quality adversarial perturbations from the historical training process.
no code implementations • 8 May 2023 • Wenyuan Yang, Yuguo Yin, Gongxi Zhu, Hanlin Gu, Lixin Fan, Xiaochun Cao, Qiang Yang
Federated learning (FL) allows multiple parties to cooperatively learn a federated model without sharing private data with each other.
no code implementations • 10 May 2023 • Wenyuan Yang, Gongxi Zhu, Yuguo Yin, Hanlin Gu, Lixin Fan, Qiang Yang, Xiaochun Cao
Federated learning allows multiple parties to collaborate in learning a global model without revealing private data.
no code implementations • 11 May 2023 • Junpei Liao, Zhikai Chen, Liang Yi, Wenyuan Yang, Baoyuan Wu, Xiaochun Cao
We apply adversarial attacks to VIF models and find that the VIF models are very vulnerable to adversarial examples.
no code implementations • journal 2023 • Zhitao Zeng, Pengwen Dai, Xuan Zhang, Lei Zhang, Xiaochun Cao
Human-object relationship detection reveals the fine-grained relationship between humans and objects, helping the comprehensive understanding of videos.
1 code implementation • 18 May 2023 • Chao Wang, Shuren Qi, Zhiqiu Huang, Yushu Zhang, Rushi Lan, Xiaochun Cao
It expands the above works on two aspects: 1) the introduced Krawtchouk basis provides better spatial-frequency discriminability and thereby is more suitable for capturing adversarial patterns than the common trigonometric or wavelet basis; 2) the extensive parameters for decomposition are generated by a pseudo-random function with secret keys, hence blocking the defense-aware adversarial attack.
no code implementations • 29 May 2023 • Junren Qin, Shanxiang Lyu, Fan Yang, Jiarui Deng, Zhihua Xia, Xiaochun Cao
In this paper, we propose a novel RDH-based static DNN watermarking scheme using quantization index modulation (QIM).
no code implementations • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023 • Jingzhi Li, Hua Zhang, Siyuan Liang, Pengwen Dai, Xiaochun Cao
Within this module, we introduce a pixel importance estimation model based on Shapley value to obtain a pixel-level attribution map, and then each pixel on the attribution map is aggregated into semantic facial parts, which are used to quantify the importance of different facial parts.
no code implementations • 22 Aug 2023 • Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao, Ranjie Duan, Jindong Gu, Rong Zhang, Hui Xue, Xiaochun Cao
In this paper, we conduct a comprehensive study of over 10 fast adversarial training methods in terms of adversarial robustness and training costs.
no code implementations • 2 Sep 2023 • Sanyi Zhang, Xiaochun Cao, Rui Wang, Guo-Jun Qi, Jie zhou
The experimental results show that the proposed method demonstrates good universality which can improve the robustness of the human parsing models and even the semantic segmentation models when facing various image common corruptions.
no code implementations • 20 Nov 2023 • Siyuan Liang, Mingli Zhu, Aishan Liu, Baoyuan Wu, Xiaochun Cao, Ee-Chien Chang
This paper reveals the threats in this practical scenario that backdoor attacks can remain effective even after defenses and introduces the \emph{\toolns} attack, which is resistant to backdoor detection and model fine-tuning defenses.
no code implementations • 27 Nov 2023 • Yunxin Li, Baotian Hu, Wei Wang, Xiaochun Cao, Min Zhang
These models predominantly map visual information into language representation space, leveraging the vast knowledge and powerful text generation abilities of LLMs to produce multimodal instruction-following responses.
no code implementations • 3 Dec 2023 • Xiaojun Jia, Jindong Gu, Yihao Huang, Simeng Qin, Qing Guo, Yang Liu, Xiaochun Cao
At the second stage, the pixels are divided into different branches based on their transferable property which is dependent on Kullback-Leibler divergence.
no code implementations • 7 Dec 2023 • Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao
Investigating the generation of high-transferability adversarial examples is crucial for uncovering VLP models' vulnerabilities in practical scenarios.
no code implementations • 8 Dec 2023 • Bangyan He, Xiaojun Jia, Siyuan Liang, Tianrui Lou, Yang Liu, Xiaochun Cao
Current Visual-Language Pre-training (VLP) models are vulnerable to adversarial examples.
no code implementations • 23 Dec 2023 • Aishan Liu, Xinwei Zhang, Yisong Xiao, Yuguang Zhou, Siyuan Liang, Jiakai Wang, Xianglong Liu, Xiaochun Cao, DaCheng Tao
This paper aims to raise awareness of the potential threats associated with applying PVMs in practical scenarios.
1 code implementation • Conference 2022 • Junyu Chen, Qianqian Xu, Zhiyong Yang, Ke Ma, Xiaochun Cao, Qingming Huang
To attack this problem, we propose a recursive meta-learning model with the user's behavior sequence prediction as a separate training task.
1 code implementation • journal 2023 • Junyu Chen, Qianqian Xu, Zhiyong Yang, Ke Ma, Xiaochun Cao, Qingming Huang
For the motif-based node representation learning process, we propose a Motif Coarsening strategy for incorporating motif structure into the graph representation learning process.
no code implementations • 31 Dec 2023 • Xinwei Liu, Xiaojun Jia, Jindong Gu, Yuan Xun, Siyuan Liang, Xiaochun Cao
However, in this paper, we propose the Few-shot Learning Backdoor Attack (FLBA) to show that FSL can still be vulnerable to backdoor attacks.
no code implementations • 2 Feb 2024 • Hao Li, Wei Wang, Cong Wang, Zhigang Luo, Xinwang Liu, Kenli Li, Xiaochun Cao
Single-domain generalized object detection aims to enhance a model's generalizability to multiple unseen target domains using only data from a single source domain during training.
no code implementations • 21 Feb 2024 • Jiawei Liang, Siyuan Liang, Man Luo, Aishan Liu, Dongchen Han, Ee-Chien Chang, Xiaochun Cao
Nevertheless, the frozen visual encoder in autoregressive VLMs imposes constraints on the learning of conventional image triggers.
no code implementations • 9 Mar 2024 • Jingyun Xue, Tao Wang, Jun Wang, Kaihao Zhang, Wenhan Luo, Wenqi Ren, Zikun Liu, Hyunhee Park, Xiaochun Cao
Specifically, we utilize sparse self-attention to filter out redundant information and noise, directing the model's attention to focus on the features more relevant to the degraded regions in need of reconstruction.
no code implementations • 15 Mar 2024 • Cong Wang, Jinshan Pan, Yeying Jin, Liyan Wang, Wei Wang, Gang Fu, Wenqi Ren, Xiaochun Cao
Our designs provide a closer look at the attention mechanism and reveal that some simple operations can significantly affect the model performance.
no code implementations • 24 Mar 2024 • Siyuan Liang, Kuanrong Liu, Jiajun Gong, Jiawei Liang, Yuan Xun, Ee-Chien Chang, Xiaochun Cao
In this paper, we explore the possibility of a less-cost defense from the perspective of model unlearning, that is, whether the model can be made to quickly \textbf{u}nlearn \textbf{b}ackdoor \textbf{t}hreats (UBT) by constructing a small set of poisoned samples.
no code implementations • 4 Apr 2024 • Shangquan Sun, Wenqi Ren, Jingyang Peng, Fenglong Song, Xiaochun Cao
Many existing methods for low-light image enhancement (LLIE) based on Retinex theory ignore important factors that affect the validity of this theory in digital imaging, such as noise, quantization error, non-linearity, and dynamic range overflow.