1 code implementation • 16 May 2022 • Tiexin Qin, Shiqi Wang, Haoliang Li
Domain generalization aims to improve the generalization capability of machine learning systems to out-of-distribution (OOD) data.
1 code implementation • 4 Apr 2022 • Chongming Gao, Wenqiang Lei, Jiawei Chen, Shiqi Wang, Xiangnan He, Shijun Li, Biao Li, Yuan Zhang, Peng Jiang
The basic idea is to first learn a causal user model on historical data to capture the overexposure effect of items on user satisfaction.
no code implementations • 20 Feb 2022 • Baoliang Chen, Lingyu Zhu, Hanwei Zhu, Wenhan Yang, Fangbo Lu, Shiqi Wang
In particular, we create a large-scale database for QUality assessment Of The Enhanced LOw-Light Image (QUOTE-LOL), which serves as the foundation in studying and developing objective quality assessment measures.
no code implementations • 20 Feb 2022 • Pingping Zhang, Xu Wang, Linwei Zhu, Yun Zhang, Shiqi Wang, Sam Kwong
In this paper, we propose a distortion-aware loop filtering model to improve the performance of intra coding for 360$^o$ videos projected via equirectangular projection (ERP) format.
no code implementations • 19 Feb 2022 • Shiqi Wang, Chongming Gao, Min Gao, Junliang Yu, Zongwei Wang, Hongzhi Yin
By providing users with opportunities to experience goods without charge, a free trial makes adopters know more about products and thus encourages their willingness to buy.
1 code implementation • 28 Jan 2022 • Yibing Liu, Haoliang Li, Yangyang Guo, Chenqi Kong, Jing Li, Shiqi Wang
Attention mechanisms are dominating the explainability of deep models.
no code implementations • 28 Jan 2022 • Yu Tian, Zhangkai Ni, Baoliang Chen, Shiqi Wang, Hanli Wang, Sam Kwong
However, little work has been dedicated to automatic quality assessment of such GAN-generated face images (GFIs), even less have been devoted to generalized and robust quality assessment of GFIs generated with unseen GAN model.
no code implementations • 31 Dec 2021 • Dongjie Ye, Zhangkai Ni, Hanli Wang, Jian Zhang, Shiqi Wang, Sam Kwong
The proposed approach is an end-to-end compressive image sensing method, composed of adaptive sampling and recovery.
no code implementations • 16 Oct 2021 • Keyan Ding, Yi Liu, Xueyi Zou, Shiqi Wang, Kede Ma
The latest advances in full-reference image quality assessment (IQA) involve unifying structure and texture similarity based on deep representations.
no code implementations • 29 Sep 2021 • huan zhang, Shiqi Wang, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J Zico Kolter
In this work, we formulate an adversarial attack using a branch-and-bound (BaB) procedure on ReLU neural networks and search adversarial examples in the activation space corresponding to binary variables in a mixed integer programming (MIP) formulation.
1 code implementation • 11 Aug 2021 • Qiuping Jiang, Zhentao Liu, Shiqi Wang, Feng Shao, Weisi Lin
Instead of explicitly formulating and fusing different masking effects in a bottom-up way, the proposed JND estimation model dedicates to first predicting a critical perceptual lossless (CPL) counterpart of the original image and then calculating the difference map between the original image and the predicted CPL image as the JND map.
1 code implementation • 9 Aug 2021 • Baoliang Chen, Lingyu Zhu, Chenqi Kong, Hanwei Zhu, Shiqi Wang, Zhu Li
In this paper, we propose a no-reference (NR) image quality assessment (IQA) method via feature level pseudo-reference (PR) hallucination.
1 code implementation • 13 Jul 2021 • Chenqi Kong, Baoliang Chen, Haoliang Li, Shiqi Wang, Anderson Rocha, Sam Kwong
The technological advancements of deep learning have enabled sophisticated face manipulation schemes, raising severe trust issues and security concerns in modern society.
no code implementations • 1 Jul 2021 • Shurun Wang, Zhao Wang, Shiqi Wang, Yan Ye
In this paper, we show that the design and optimization of network architecture could be further improved for compression towards machine vision.
no code implementations • NeurIPS 2021 • Shiqi Wang, huan zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J Zico Kolter
We develop $\beta$-CROWN, a new bound propagation based method that can fully encode neuron split constraints in branch-and-bound (BaB) based complete verification via optimizable parameters $\beta$.
1 code implementation • 24 May 2021 • Yizheng Chen, Shiqi Wang, Yue Qin, Xiaojing Liao, Suman Jana, David Wagner
Since data distribution shift is very common in security applications, e. g., often observed for malware detection, local robustness cannot guarantee that the property holds for unseen inputs at the time of deploying the classifier.
no code implementations • 14 May 2021 • Chris Xing Tian, Haoliang Li, YuFei Wang, Shiqi Wang
However, due to the issue of limited dataset availability and the strict legal and ethical requirements for patient privacy protection, the broad applications of medical imaging classification driven by DNN with large-scale training data have been largely hindered.
3 code implementations • NeurIPS 2021 • Shiqi Wang, huan zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
Compared to the typically tightest but very costly semidefinite programming (SDP) based incomplete verifiers, we obtain higher verified accuracy with three orders of magnitudes less verification time.
no code implementations • 27 Feb 2021 • Chris Xing Tian, Haoliang Li, Xiaofei Xie, Yang Liu, Shiqi Wang
More specifically, by treating the DNN as a program and each neuron as a functional point of the code, during the network training we aim to improve the generalization capability by maximizing the neuron coverage of DNN with the gradient similarity regularization between the original and augmented samples.
no code implementations • 25 Jan 2021 • Baoliang Chen, Wenhan Yang, Haoliang Li, Shiqi Wang, Sam Kwong
The first branch aims to learn the camera invariant spoofing features via feature level decomposition in the high frequency domain.
1 code implementation • 30 Dec 2020 • Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong
In this paper, we present an unsupervised image enhancement generative adversarial network (UEGAN), which learns the corresponding image-to-image mapping from a set of images with desired characteristics in an unsupervised manner, rather than learning on a large number of paired images.
no code implementations • 30 Dec 2020 • Zhangkai Ni, Wenhan Yang, Shiqi Wang, Lin Ma, Sam Kwong
The key novelty of the proposed QAGAN lies in the injected QAM for the generator such that it learns domain-relevant quality attention directly from the two domains.
1 code implementation • 27 Dec 2020 • Baoliang Chen, Lingyu Zhu, Guo Li, Hongfei Fan, Shiqi Wang
In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and -frame rate quality prediction.
no code implementations • 14 Dec 2020 • Shiqi Wang, Kevin Eykholt, Taesung Lee, Jiyong Jang, Ian Molloy
On CIFAR10, a non-robust LeNet model has a 21. 63% error rate, while a model created using verifiable training and a L-infinity robustness criterion of 8/255, has an error rate of 57. 10%.
2 code implementations • ICLR 2021 • Kaidi Xu, huan zhang, Shiqi Wang, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh
Formal verification of neural networks (NNs) is a challenging and important problem.
2 code implementations • 10 Nov 2020 • Jianhui Chang, Zhenghui Zhao, Chuanmin Jia, Shiqi Wang, Lingbo Yang, Qi Mao, Jian Zhang, Siwei Ma
To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.
1 code implementation • NeurIPS 2020 • Haoliang Li, YuFei Wang, Renjie Wan, Shiqi Wang, Tie-Qiang Li, Alex C. Kot
Recently, we have witnessed great progress in the field of medical imaging classification by adopting deep neural networks.
no code implementations • 16 Sep 2020 • Rizhao Cai, Haoliang Li, Shiqi Wang, Changsheng chen, Alex ChiChung Kot
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i. e., to glance at the example globally first and then carefully observe the local regions to gain more discriminative information, for the face anti-spoofing problem, we propose a novel framework based on the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN).
no code implementations • 15 Sep 2020 • Haoliang Li, Yufei Wang, Xiaofei Xie, Yang Liu, Shiqi Wang, Renjie Wan, Lap-Pui Chau, Alex C. Kot
In this paper, we propose a novel black-box backdoor attack technique on face recognition systems, which can be conducted without the knowledge of the targeted DNN model.
no code implementations • 19 Aug 2020 • Baoliang Chen, Haoliang Li, Hongfei Fan, Shiqi Wang
Here, we develop the first unsupervised domain adaptation based no reference quality assessment method for SCIs, leveraging rich subjective ratings of the natural images (NIs).
no code implementations • 13 Aug 2020 • Rongqun Lin, Linwei Zhu, Shiqi Wang, Sam Kwong
Compactly representing the visual signals is of fundamental importance in various image/video-centered applications.
no code implementations • 4 Jun 2020 • Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin
Current neural-network-based classifiers are susceptible to adversarial examples.
1 code implementation • 20 May 2020 • Yuqing Liu, Shiqi Wang, Jian Zhang, Shanshe Wang, Siwei Ma, Wen Gao
A novel iterative super-resolution network (ISRN) is proposed on top of the iterative optimization.
1 code implementation • 4 May 2020 • Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli
The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments.
no code implementations • 21 Apr 2020 • Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao
In particular, we study the feature and texture compression in a scalable coding framework, where the base layer serves as the deep learning feature and enhancement layer targets to perfectly reconstruct the texture.
2 code implementations • 16 Apr 2020 • Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli
Objective measures of image quality generally operate by comparing pixels of a "degraded" image to those of the original.
1 code implementation • 6 Mar 2020 • Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana
Recent research has proposed the lottery ticket hypothesis, suggesting that for a deep neural network, there exist trainable sub-networks performing equally or better than the original model with commensurate training steps.
2 code implementations • NeurIPS 2020 • Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
We demonstrate that our approach, titled HYDRA, achieves compressed networks with state-of-the-art benign and robust accuracy, simultaneously.
no code implementations • NeurIPS 2020 • Jiahao Su, Shiqi Wang, Furong Huang
In this work, we propose to replace any traditional convolutional layer with an autoregressive moving-average (ARMA) layer, a novel module with an adjustable receptive field controlled by the learnable autoregressive coefficients.
no code implementations • 10 Feb 2020 • Shurun Wang, Wenhan Yang, Shiqi Wang
In this paper, we propose a novel end-to-end feature compression scheme by leveraging the representation and learning capability of deep neural networks, towards intelligent front-end equipped analysis with promising accuracy and efficiency.
no code implementations • 16 Dec 2019 • Wenhan Yang, Robby T. Tan, Shiqi Wang, Yuming Fang, Jiaying Liu
The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation.
1 code implementation • 3 Dec 2019 • Yizheng Chen, Shiqi Wang, Weifan Jiang, Asaf Cidon, Suman Jana
There are various costs for attackers to manipulate the features of security classifiers.
1 code implementation • 31 Jul 2019 • Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao
The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelligent sensing manner.
1 code implementation • 3 Jul 2019 • Keyan Ding, Kede Ma, Shiqi Wang
The goal of research in automatic image popularity assessment (IPA) is to develop computational models that can accurately predict the potential of a social image to go viral on the Internet.
no code implementations • 14 Jun 2019 • Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana
In this work, we rigorously study the extension of network pruning strategies to preserve both benign accuracy and robustness of a network.
no code implementations • 5 Jun 2019 • Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana
In this paper, we present interval attacks, a new technique to find adversarial examples to evaluate the robustness of neural networks.
no code implementations • 3 Jun 2019 • Junlong Gao, Xi Meng, Shiqi Wang, Xia Li, Shanshe Wang, Siwei Ma, Wen Gao
Existing captioning models often adopt the encoder-decoder architecture, where the decoder uses autoregressive decoding to generate captions, such that each token is generated sequentially given the preceding generated tokens.
no code implementations • 16 Apr 2019 • Minghao Yin, Xiu Li, Yongbing Zhang, Shiqi Wang
In this paper, we aim to understand Residual Network (ResNet) in a scientifically sound way by providing a bridge between ResNet and Feynman path integral.
no code implementations • CVPR 2019 • Junlong Gao, Shiqi Wang, Shanshe Wang, Siwei Ma, Wen Gao
Existing methods for image captioning are usually trained by cross entropy loss, which leads to exposure bias and the inconsistency between the optimizing function and evaluation metrics.
no code implementations • 7 Apr 2019 • Siwei Ma, Xinfeng Zhang, Chuanmin Jia, Zhenghui Zhao, Shiqi Wang, Shanshe Wang
Deep convolution neural network (CNN) which makes the neural network resurge in recent years and has achieved great success in both artificial intelligent and signal processing fields, also provides a novel and promising solution for image and video compression.
1 code implementation • 6 Apr 2019 • Yizheng Chen, Shiqi Wang, Dongdong She, Suman Jana
A practically useful malware classifier must be robust against evasion attacks.
no code implementations • 14 Mar 2019 • Shurun Wang, Shiqi Wang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Wen Gao
In this paper, we propose a scalable image compression scheme, including the base layer for feature representation and enhancement layer for texture representation.
1 code implementation • 6 Nov 2018 • Shiqi Wang, Yizheng Chen, Ahmed Abdou, Suman Jana
Making neural networks robust against adversarial inputs has resulted in an arms race between new defenses and attacks.
2 code implementations • NeurIPS 2018 • Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana
Our approach can check different safety properties and find concrete counterexamples for networks that are 10$\times$ larger than the ones supported by existing analysis techniques.
no code implementations • 17 Sep 2018 • Zhuo Chen, Weisi Lin, Shiqi Wang, Ling-Yu Duan, Alex C. Kot
The recent advances of hardware technology have made the intelligent analysis equipped at the front-end with deep learning more prevailing and practical.
no code implementations • CVPR 2018 • Haoliang Li, Sinno Jialin Pan, Shiqi Wang, Alex C. Kot
In this paper, we tackle the problem of domain generalization: how to learn a generalized feature representation for an âunseenâ target domain by taking the advantage of multiple seen source-domain data.
Ranked #25 on
Domain Generalization
on PACS
3 code implementations • 28 Apr 2018 • Shiqi Wang, Kexin Pei, Justin Whitehouse, Junfeng Yang, Suman Jana
In this paper, we present a new direction for formally checking security properties of DNNs without using SMT solvers.
no code implementations • 5 Dec 2017 • Ling-Yu Duan, Yihang Lou, Shiqi Wang, Wen Gao, Yong Rui
To practically facilitate deep neural network models in the large-scale video analysis, there are still unprecedented challenges for the large-scale video data management.
no code implementations • 25 Sep 2017 • Chuanmin Jia, Shiqi Wang, Xinfeng Zhang, Shanshe Wang, Siwei Ma
Deep learning has demonstrated tremendous break through in the area of image/video processing.
Multimedia
3 code implementations • 13 Aug 2017 • Zhuo Chen, Weisi Lin, Shiqi Wang, Long Xu, Leida Li
For many computer vision problems, the deep neural networks are trained and validated based on the assumption that the input images are pristine (i. e., artifact-free).
no code implementations • 26 Apr 2017 • Ling-Yu Duan, Vijay Chandrasekhar, Shiqi Wang, Yihang Lou, Jie Lin, Yan Bai, Tiejun Huang, Alex ChiChung Kot, Wen Gao
This paper provides an overview of the on-going compact descriptors for video analysis standard (CDVA) from the ISO/IEC moving pictures experts group (MPEG).
no code implementations • 1 Mar 2017 • Yan Bai, Feng Gao, Yihang Lou, Shiqi Wang, Tiejun Huang, Ling-Yu Duan
In this paper, we propose to leverage intra-class variance in metric learning of triplet network to improve the performance of fine-grained recognition.
no code implementations • 1 Mar 2017 • Feng Gao, Yihang Lou, Yan Bai, Shiqi Wang, Tiejun Huang, Ling-Yu Duan
Object detection aims to identify instances of semantic objects of a certain class in images or videos.
no code implementations • 17 Aug 2016 • Xiang Zhang, Jiarui Sun, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao
Therefore, introducing an accurate rate-constraint in sparse coding and dictionary learning becomes meaningful, which has not been fully exploited in the context of sparse representation.