no code implementations • ECCV 2020 • Fan Wang, Huidong Liu, Dimitris Samaras, Chao Chen
We show in experiments that our method generates synthetic images with realistic topology.
no code implementations • 25 Jan 2023 • Chengqian Ma, Zhiqiang Wu, Chunlei Cai, Pengwei Zhang, Yi Wang, Long Zheng, Chao Chen, Quan Zhou
In the past decades, lots of progress have been done in the video compression field including traditional video codec and learning-based video codec.
no code implementations • 28 Dec 2022 • Chao Chen, Chenghua Guo, Guixiang Ma, Xi Zhang, Sihong Xie
Gradient-based explanation is the cornerstone of explainable deep networks, but it has been shown to be vulnerable to adversarial attacks.
no code implementations • 13 Dec 2022 • Chao Chen, Xinhao Liu, Yiming Li, Li Ding, Chen Feng
LiDAR mapping is important yet challenging in self-driving and mobile robotics.
1 code implementation • 1 Dec 2022 • Yulei Qin, Xingyu Chen, Chao Chen, Yunhang Shen, Bo Ren, Yun Gu, Jie Yang, Chunhua Shen
Most existing methods focus on learning noise-robust models from web images while neglecting the performance drop caused by the differences between web domain and real-world domain.
1 code implementation • 30 Nov 2022 • Jie Liu, Chao Chen, Jie Tang, Gangshan Wu
In the fine area, we use an Intra-Patch Self-Attention (IPSA) module to model long-range pixel dependencies in a local patch, and then a $3\times3$ convolution is applied to process the finest details.
no code implementations • 22 Nov 2022 • Lu Pang, Tao Sun, Haibin Ling, Chao Chen
It is crucial to defend against such attacks, i. e., to postprocess a suspicious model so that its backdoor behavior is mitigated while its normal prediction power on clean inputs remain uncompromised.
no code implementations • 25 Sep 2022 • Dongli Tan, Jiang-Jiang Liu, Xingyu Chen, Chao Chen, Ruixin Zhang, Yunhang Shen, Shouhong Ding, Rongrong Ji
In this paper, we propose an efficient structure named Efficient Correspondence Transformer (ECO-TR) by finding correspondences in a coarse-to-fine manner, which significantly improves the efficiency of functional correspondence model.
no code implementations • 17 Sep 2022 • Sei Zhen Khong, Chao Chen
In this paper, we propose a notion of dissipativity with dynamic supply rates for nonlinear differential input-state-output equations via the use of auxiliary systems.
no code implementations • 31 Aug 2022 • Chao Chen, Dawei Wang, Feng Mao, Zongzhang Zhang, Yang Yu
Semi-supervised Anomaly Detection (AD) is a kind of data mining task which aims at learning features from partially-labeled datasets to help detect outliers.
no code implementations • 19 Aug 2022 • Chao Chen, Xinhao Liu, Xuchu Xu, Yiming Li, Li Ding, Ruoyu Wang, Chen Feng
Inspired by noisy label learning, we propose a novel self-supervised framework named \textit{TF-VPR} that uses temporal neighborhoods and learnable feature neighborhoods to discover unknown spatial neighborhoods.
no code implementations • 9 Aug 2022 • Weimin Lyu, Xinyu Dong, Rachel Wong, Songzhu Zheng, Kayley Abell-Hart, Fusheng Wang, Chao Chen
Deep-learning-based clinical decision support using structured electronic health records (EHR) has been an active research area for predicting risks of mortality and diseases.
no code implementations • 9 Aug 2022 • Weimin Lyu, Songzhu Zheng, Tengfei Ma, Haibin Ling, Chao Chen
Trojan attacks pose a severe threat to AI systems.
no code implementations • 28 Jul 2022 • Zijue Chen, Keenan Granland, Rhys Newbury, Chao Chen
We further validated HOB-CNN against two different types of 2D trees, and HOB-CNN shows generalization across different trees and robustness under different occluded conditions.
1 code implementation • 20 Jul 2022 • Saumya Gupta, Xiaoling Hu, James Kaan, Michael Jin, Mutshipay Mpoy, Katherine Chung, Gagandeep Singh, Mary Saltz, Tahsin Kurc, Joel Saltz, Apostolos Tassiopoulos, Prateek Prasanna, Chao Chen
In this paper, we introduce a novel topological interaction module to encode the topological interactions into a deep neural network.
1 code implementation • 18 Jul 2022 • Zequn Qin, Jingyu Chen, Chao Chen, Xiaozhi Chen, Xi Li
Bird's eye view (BEV) representation is a new perception formulation for autonomous driving, which is based on spatial fusion.
1 code implementation • 18 Jul 2022 • Chao Chen, Yu-Shen Liu, Zhizhong Han
Our insight here is that both the part learning and the part blending can be conducted much easier in the latent space than in the spatial space.
no code implementations • 10 Jul 2022 • Lin Li, Chao Chen, Lei Pan, Yonghang Tai, Jun Zhang, Yang Xiang
It reduces the success rate of rPPG spoofing attacks in user authentication to 0. 05.
no code implementations • RA-L 2022 • Fuqiang Gu, Yong Lee, Yuan Zhuang, You Li, Jingbin Liu, Fangwen Yu, Ruiyuan Li, Chao Chen
Event-based sensors (e. g., DVS cameras) are capable of higher dynamic range, higher temporal resolution, lower time latency, and better power efficiency compared to conventional devices (e. g., RGB cameras).
no code implementations • 6 Jun 2022 • Yikai Zhang, Jiachen Yao, Yusu Wang, Chao Chen
Topological loss based on persistent homology has shown promise in various applications.
no code implementations • 3 Jun 2022 • Xiaoling Hu, Dimitris Samaras, Chao Chen
We use discrete Morse theory and persistent homology to construct an one-parameter family of structures as the topological/structural representation space.
no code implementations • 21 May 2022 • Chao Chen, Zijian Gao, Kele Xu, Sen yang, Yiying Li, Bo Ding, Dawei Feng, Huaimin Wang
To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in handy for pursuing the rewards in the future, such as encouraging the agent to visit novel states.
1 code implementation • NAACL 2022 • Weimin Lyu, Songzhu Zheng, Tengfei Ma, Chao Chen
Trojan attacks raise serious security concerns.
2 code implementations • 11 May 2022 • Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang
The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.
no code implementations • 23 Apr 2022 • Mahmudul Hasan, Jakub R. Kaczmarzyk, David Paredes, Lyanne Oblein, Jaymie Oentoro, Shahira Abousamra, Michael Horowitz, Dimitris Samaras, Chao Chen, Tahsin Kurc, Kenneth R. Shroyer, Joel Saltz
Understanding the impact of tumor biology on the composition of nearby cells often requires characterizing the impact of biologically distinct tumor regions.
1 code implementation • IEEE Transactions on Knowledge and Data Engineering 2021 • Chao Chen, Dongsheng Li, Junchi Yan, Xiaokang Yang
Capturing the dynamics in user preference is crucial to better predict user future behaviors because user preferences often drift over time.
1 code implementation • 2 Apr 2022 • Jing He, Yiyi Zhou, Qi Zhang, Jun Peng, Yunhang Shen, Xiaoshuai Sun, Chao Chen, Rongrong Ji
Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation.
1 code implementation • 1 Apr 2022 • Mingrui Wu, Jiaxin Gu, Yunhang Shen, Mingbao Lin, Chao Chen, Xiaoshuai Sun
Extensive experiments on HICO-Det dataset demonstrate that our model discovers potential interactive pairs and enables the recognition of unseen HOIs.
Human-Object Interaction Detection
Knowledge Distillation
+3
1 code implementation • 30 Mar 2022 • Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang
User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data.
2 code implementations • 30 Mar 2022 • Chaoyang Zhu, Yiyi Zhou, Yunhang Shen, Gen Luo, Xingjia Pan, Mingbao Lin, Chao Chen, Liujuan Cao, Xiaoshuai Sun, Rongrong Ji
In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e. g., phrase localization, referring expression comprehension (REC) and segmentation (RES).
no code implementations • 29 Mar 2022 • Chao Chen, Xiaowei Jin, Hui Li
The partial differential equation (PDE) plays a significantly important role in many fields of science and engineering.
no code implementations • 24 Mar 2022 • Wenjia Zhang, Yikai Zhang, Xiaoling Hu, Mayank Goswami, Chao Chen, Dimitris Metaxas
Assuming data lies in a manifold, we investigate two new types of adversarial risk, the normal adversarial risk due to perturbation along normal direction, and the in-manifold adversarial risk due to perturbation within the manifold.
no code implementations • CVPR 2022 • Aishik Konwer, Xuan Xu, Joseph Bae, Chao Chen, Prateek Prasanna
In our method, a self-attention based Temporal Convolutional Network (TCN) is used to learn a representation that is most reflective of the disease trajectory.
no code implementations • 7 Feb 2022 • Jiaqi Yang, Xiaoling Hu, Chao Chen, Chialing Tsai
We propose a novel TopologyAttention ConvLSTM Network (TACNet) for 3D image segmentation in order to achieve high structural accuracy for 3D segmentation tasks.
1 code implementation • 28 Jan 2022 • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen
Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods.
1 code implementation • 18 Jan 2022 • Chao Chen, Yibing Zhan, Baosheng Yu, Liu Liu, Yong Luo, Bo Du
To address this problem, we propose Resistance Training using Prior Bias (RTPB) for the scene graph generation.
no code implementations • CVPR 2022 • Mingrui Wu, Xuying Zhang, Xiaoshuai Sun, Yiyi Zhou, Chao Chen, Jiaxin Gu, Xing Sun, Rongrong Ji
Current Image captioning (IC) methods predict textual words sequentially based on the input visual information from the visual feature extractor and the partially generated sentence information.
no code implementations • 8 Dec 2021 • Hanwen Kang, Xing Wang, Chao Chen
It is vital for robots to recognise and localise fruits before the harvesting in natural orchards.
no code implementations • 6 Dec 2021 • Wenjie Chu, Shen Li, Chao Chen, Longfei Xu, Hengbin Cui, Kaikui Liu
Most of the existing methods for debaising in click-through rate (CTR) prediction depend on an oversimplified assumption, i. e., the click probability is the product of observation probability and relevance probability.
no code implementations • 29 Nov 2021 • Yifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, Sihong Xie
We design a user study to investigate such joint effects and use the findings to design a multi-objective optimization (MOO) algorithm to find Pareto optimal explanations that are well-balanced in simulatability and counterfactual.
no code implementations • 20 Nov 2021 • Liling Zhang, Xinyu Lei, Yichun Shi, Hongyu Huang, Chao Chen
Federated Learning (FL) enables a group of clients to jointly train a machine learning model with the help of a centralized server.
no code implementations • 20 Oct 2021 • Ran Cheng, Chao Chen, Longfei Xu, Shen Li, Lei Wang, Hengbin Cui, Kaikui Liu, Xiaolong Li
For user representation, we utilize a series of historical navigation to extract user preference.
no code implementations • ICLR 2022 • Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen
Despite their success and popularity, deep neural networks (DNNs) are vulnerable when facing backdoor attacks.
1 code implementation • ICCV 2021 • Shahira Abousamra, David Belinsky, John Van Arnam, Felicia Allard, Eric Yee, Rajarsi Gupta, Tahsin Kurc, Dimitris Samaras, Joel Saltz, Chao Chen
In digital pathology, both detection and classification of cells are important for automatic diagnostic and prognostic tasks.
1 code implementation • 6 Oct 2021 • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen
In this paper, we consider rules as cycles and show that the space of cycles has a unique structure based on the mathematics of algebraic topology.
no code implementations • 30 Sep 2021 • Di Zhao, Chao Chen, Sei Zhen Khong
In this study, we extend the theory of negative imaginary (NI) systems to a nonlinear framework using a frequency-domain approach.
no code implementations • 29 Sep 2021 • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen
We propose to collect cycle bases that span the space of cycles.
no code implementations • 29 Sep 2021 • Anthony Opipari, Jana Pavlasek, Chao Chen, Shoutian Wang, Karthik Desingh, Odest Jenkins
By combining differentiable neural networks with an efficient belief propagation algorithm, our method learns to maintain a set of marginal posterior samples using end-to-end training.
no code implementations • 29 Sep 2021 • Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Yuriy Nevmyvaka, Chao Chen
Learning and decision making in domains with naturally high noise-to-signal ratios – such as Finance or Public Health – can be challenging and yet extremely important.
no code implementations • 15 Sep 2021 • Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie
Learning to compare two objects are essential in applications, such as digital forensics, face recognition, and brain network analysis, especially when labeled data is scarce and imbalanced.
no code implementations • 3 Sep 2021 • Chao Chen, Wei Chen, Di Zhao, Sei Zhen Khong, Li Qiu
It is, thus, different from the recently appeared nonlinear system phase which adopts the complexification of real-valued signals using the Hilbert transform.
no code implementations • NeurIPS 2021 • Songzhu Zheng, Yikai Zhang, Hubert Wagner, Mayank Goswami, Chao Chen
Deep neural networks are known to have security issues.
no code implementations • 20 May 2021 • Li-Heng Chen, Christos G. Bampis, Zhi Li, Chao Chen, Alan C. Bovik
The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values.
1 code implementation • AAAI 2021 • Chao Chen, Dongsheng Li, Junchi Yan, Hanchi Huang, Xiaokang Yang
One-bit matrix completion is an important class of positiveunlabeled (PU) learning problems where the observations consist of only positive examples, eg, in top-N recommender systems.
1 code implementation • 13 May 2021 • Fan Wang, Saarthak Kapse, Steven Liu, Prateek Prasanna, Chao Chen
Characterization of breast parenchyma on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures.
no code implementations • 13 May 2021 • XiaoYu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, Yang Xiang
This survey presents the most recent findings of privacy attacks and defenses appeared in cloud-based neural network services.
1 code implementation • 12 May 2021 • Jinming Su, Chao Chen, Ke Zhang, Junfeng Luo, Xiaoming Wei, Xiaolin Wei
Next, multi-level structural constraints are used to improve the perception of lanes.
Ranked #15 on
Lane Detection
on CULane
no code implementations • 15 Apr 2021 • Dongsheng Li, Haodong Liu, Chao Chen, Yingying Zhao, Stephen M. Chu, Bo Yang
In collaborative filtering (CF) algorithms, the optimal models are usually learned by globally minimizing the empirical risks averaged over all the observed data.
1 code implementation • 4 Apr 2021 • Chao Chen, Catalina Raymond, Bill Speier, Xinyu Jin, Timothy F. Cloughesy, Dieter Enzmann, Benjamin M. Ellingson, Corey W. Arnold
To alleviate the data imbalance problem between normal tissues and the tumor regions, we introduce a local loss to improve the contribution of the tumor regions, which leads to better enhancement results on tumors.
no code implementations • ICLR 2021 • Xiaoling Hu, Yusu Wang, Li Fuxin, Dimitris Samaras, Chao Chen
In the segmentation of fine-scale structures from natural and biomedical images, per-pixel accuracy is not the only metric of concern.
1 code implementation • ICLR 2021 • Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
Label noise is frequently observed in real-world large-scale datasets.
Ranked #8 on
Learning with noisy labels
on ANIMAL
no code implementations • 11 Mar 2021 • Girish Mururu, Chao Chen, Chris Porter, Santosh Pande, Ada Gavrilovska
Typical schedulers in multi-tenancy environments make use of reactive, feedback-oriented mechanisms based on performance counters to avoid resource contention but suffer from detection lag and loss of performance.
Distributed, Parallel, and Cluster Computing
1 code implementation • 20 Feb 2021 • Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen
Link prediction is an important learning task for graph-structured data.
2 code implementations • 16 Feb 2021 • Yuantian Miao, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, Yang Xiang
Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years.
no code implementations • 10 Feb 2021 • Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami
This raises the question: is the stability analysis of [18] tight for smooth functions, and if not, for what kind of loss functions and data distributions can the stability analysis be improved?
1 code implementation • 9 Feb 2021 • Yikai Zhang, Hui Qu, Qi Chang, Huidong Liu, Dimitris Metaxas, Chao Chen
A federatedGAN jointly trains a centralized generator and multiple private discriminators hosted at different sites.
1 code implementation • ICCV 2021 • Chao Chen, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker
Our method pushes the neural network to generate a 3D point cloud whose 2D projections match the irregular point supervision from different view angles.
no code implementations • 1 Jan 2021 • Ze Ye, Tengfei Ma, Chien-Chun Ni, Kin Sum Liu, Jie Gao, Chao Chen
We propose a novel GNN defense algorithm against structural attacks that maliciously modify graph topology.
no code implementations • 1 Jan 2021 • Yikai Zhang, Samuel Bald, Wenjia Zhang, Vamsi Pritham Pingali, Chao Chen, Mayank Goswami
We provide empirical evidence that this condition holds for several loss functions, and provide theoretical evidence that the known tight SGD stability bounds for convex and non-convex loss functions can be circumvented by HC loss functions, thus partially explaining the generalization of deep neural networks.
1 code implementation • 23 Dec 2020 • Shahira Abousamra, Minh Hoai, Dimitris Samaras, Chao Chen
Due to various challenges, a localization method is prone to spatial semantic errors, i. e., predicting multiple dots within a same person or collapsing multiple dots in a cluttered region.
1 code implementation • NeurIPS 2020 • Pengxiang Wu, Songzhu Zheng, Mayank Goswami, Dimitris Metaxas, Chao Chen
Noisy labels can impair the performance of deep neural networks.
no code implementations • 30 Nov 2020 • Chao Chen, Di Zhao, Wei Chen, Sei Zhen Khong, Li Qiu
A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems.
3 code implementations • ICML 2020 • Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen
To be robust against label noise, many successful methods rely on the noisy classifiers (i. e., models trained on the noisy training data) to determine whether a label is trustworthy.
Ranked #38 on
Image Classification
on Clothing1M
2 code implementations • 16 Nov 2020 • Chao Chen, Tianyu Liang, George Biros
We introduce a randomized algorithm, namely RCHOL, to construct an approximate Cholesky factorization for a given Laplacian matrix (a. k. a., graph Laplacian).
Numerical Analysis Mathematical Software Numerical Analysis
no code implementations • 16 Oct 2020 • Keenan Granland, Rhys Newbury, David Ting, Chao Chen
It is shown that in our application, the new Automating-the-Loop method greatly reduces the labeling effort while producing comparable performance to both human-in-the-loop and complete manual labeling methods.
no code implementations • 14 Oct 2020 • Zijue Chen, David Ting, Rhys Newbury, Chao Chen
DeepLabv3 outperforms the other models at Binary accuracy, Mean IoU and Boundary F1 score, but is surpassed by Pix2Pix (without discriminator) and U-Net in Occluded branch recall.
1 code implementation • NeurIPS 2020 • Jialin Yuan, Chao Chen, Li Fuxin
Specifically, we propose a variational relaxation of instance segmentation as minimizing an optimization functional for a piecewise-constant segmentation problem, which can be used to train an FCN end-to-end.
no code implementations • 18 Jul 2020 • Zhiyong Yu, Lei Han, Chao Chen, Wenzhong Guo, Zhiwen Yu
This paper proposes a strategy named IHMs (Intermediate Searching at Heuristic Moments): each step we figure out which moment is the best to search according to a heuristic indicator, then at that moment search locations one by one in descending order of predicted appearing probabilities, until a search hits; iterate this step until we get the object's current location.
1 code implementation • ECCV 2020 • Hui Qu, Yikai Zhang, Qi Chang, Zhennan Yan, Chao Chen, Dimitris Metaxas
Our proposed method tackles the challenge of training GAN in the federated learning manner: How to update the generator with a flow of temporary discriminators?
no code implementations • ICML 2020 • Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker
To optimize 3D shape parameters, current renderers rely on pixel-wise losses between rendered images of 3D reconstructions and ground truth images from corresponding viewpoints.
no code implementations • 28 Jun 2020 • Abdelkader Nasreddine Belkacem, Sofia Ouhbi, Abderrahmane Lakas, Elhadj Benkhelifa, Chao Chen
Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus.
no code implementations • 27 Jun 2020 • Wei Wang, Gangqiang Hu, Bo Yuan, Shandong Ye, Chao Chen, YaYun Cui, Xi Zhang, Liting Qian
To illustrate the importance of prior knowledge, the result of the algorithm without prior knowledge is also investigated.
1 code implementation • 30 May 2020 • Chao Chen, Zhihong Chen, Xinyu Jin, Lanjuan Li, William Speier, Corey W. Arnold
However, training with the global image underutilizes discriminative local information, while providing extra annotations is expensive and subjective.
1 code implementation • CVPR 2020 • Qi Chang, Hui Qu, Yikai Zhang, Mert Sabuncu, Chao Chen, Tong Zhang, Dimitris Metaxas
In this paper, we propose a data privacy-preserving and communication efficient distributed GAN learning framework named Distributed Asynchronized Discriminator GAN (AsynDGAN).
no code implementations • ICLR 2020 • Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen
Graph-structured data is prevalent in many domains.
no code implementations • 21 Apr 2020 • Yifei Liu, Chao Chen, Xi Zhang, Sihong Xie
There is no existing method to rigorously attribute the inference outcomes to the contributing factors of the graphical models.
no code implementations • 30 Mar 2020 • Hanwen Kang, Chao Chen
In this research, a fully neural network based visual perception framework for autonomous apple harvesting is proposed.
no code implementations • 29 Dec 2019 • Hanwen Kang, Chao Chen
This paper develops a framework of visual perception and modelling for robotic harvesting of fruits in the orchard environments.
1 code implementation • 27 Dec 2019 • Chao Chen, Zhihang Fu, Zhihong Chen, Sheng Jin, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua
In particular, our proposed HoMM can perform arbitrary-order moment tensor matching, we show that the first-order HoMM is equivalent to Maximum Mean Discrepancy (MMD) and the second-order HoMM is equivalent to Correlation Alignment (CORAL).
no code implementations • 28 Nov 2019 • Hanwen Kang, Chao Chen
The robustness and efficiency of the DaSNet-V2 in detection and segmentation are validated by the experiments in the real-environment of apple orchard.
no code implementations • 25 Nov 2019 • Pengxiang Wu, Chao Chen, Jingru Yi, Dimitris Metaxas
The spatial layout of the beams is regular, and this allows the beam features to be further fed into an efficient 2D convolutional neural network (CNN) for hierarchical feature aggregation.
no code implementations • 20 Nov 2019 • Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua
In this paper, we propose a novel Semi-supervised Self-pace Adversarial Hashing method, named SSAH to solve the above problems in a unified framework.
no code implementations • 25 Sep 2019 • Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen
To collect large scale annotated data, it is inevitable to introduce label noise, i. e., incorrect class labels.
no code implementations • 25 Sep 2019 • Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang, Zhu Han
In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories.
no code implementations • 13 Aug 2019 • Chao Chen, Yifei Liu, Xi Zhang, Sihong Xie
Probabilistic inferences distill knowledge from graphs to aid human make important decisions.
no code implementations • 7 Aug 2019 • Bin Guo, Huihui Chen, Yan Liu, Chao Chen, Qi Han, Zhiwen Yu
A generic model for CrowdMining is further proposed based on a set of existing studies.
no code implementations • 31 Jul 2019 • Zhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker
Specifically, ShapeCaptioner aggregates the parts detected in multiple colored views using our novel part class specific aggregation to represent a 3D shape, and then, employs a sequence to sequence model to generate the caption.
no code implementations • 9 Jul 2019 • Shahira Abousamra, Le Hou, Rajarsi Gupta, Chao Chen, Dimitris Samaras, Tahsin Kurc, Rebecca Batiste, Tianhao Zhao, Shroyer Kenneth, Joel Saltz
This allows for a much larger training set, that reflects visual variability across multiple cancer types and thus training of a single network which can be automatically applied to each cancer type without human adjustment.
2 code implementations • NeurIPS 2019 • Xiaoling Hu, Li Fuxin, Dimitris Samaras, Chao Chen
Segmentation algorithms are prone to make topological errors on fine-scale structures, e. g., broken connections.
no code implementations • 12 Jun 2019 • Sheng Chen, Xu Wang, Chao Chen, Yifan Lu, Xijin Zhang, Linfu Wen
In this paper, we pursue very efficient neural network modules which can significantly boost the learning power of deep convolutional neural networks with negligible extra computational cost.
no code implementations • CVPR 2019 • Chao Chen, Guanbin Li, Ruijia Xu, Tianshui Chen, Meng Wang, Liang Lin
Current neural networks for 3D object recognition are vulnerable to 3D rotation.
no code implementations • CVPR 2020 • Zhihong Chen, Chao Chen, Zhaowei Cheng, Boyuan Jiang, Ke Fang, Xinyu Jin
However, since the domain shift between source and target domains, only using the deep features for sample selection is defective.
Ranked #5 on
Partial Domain Adaptation
on Office-31
no code implementations • 15 May 2019 • Chongyang Bai, Maksim Bolonkin, Judee Burgoon, Chao Chen, Norah Dunbar, Bharat Singh, V. S. Subrahmanian, Zhe Wu
Most work on automated deception detection (ADD) in video has two restrictions: (i) it focuses on a video of one person, and (ii) it focuses on a single act of deception in a one or two minute video.
no code implementations • 3 May 2019 • Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu
The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.
Materials Science
no code implementations • 13 Apr 2019 • Chao Chen, Zhihang Fu, Zhihong Chen, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua
Recent advances in unsupervised domain adaptation mainly focus on learning shared representations by global distribution alignment without considering class information across domains.
3 code implementations • 6 Mar 2019 • Ruoxi Wang, Chao Chen, Jonghyun Lee, Eric Darve
We introduce a parallel method that provably requires $O(N)$ operations to reduce the computation cost.
Mathematical Software
1 code implementation • 9 Jan 2019 • Léopold Cambier, Chao Chen, Erik G Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, Eric Darve
We evaluate the algorithm on some large problems show it exhibits near-linear scaling.
Numerical Analysis
no code implementations • 11 Dec 2018 • Weikai Chen, Xiaoguang Han, Guanbin Li, Chao Chen, Jun Xing, Yajie Zhao, Hao Li
Three-dimensional object recognition has recently achieved great progress thanks to the development of effective point cloud-based learning frameworks, such as PointNet and its extensions.
no code implementations • 20 Nov 2018 • Chao Chen, Sheng Zhang, Cuibing Du
Change detection has been a challenging visual task due to the dynamic nature of real-world scenes.
no code implementations • 6 Nov 2018 • Dongsheng Li, Chao Chen, Qin Lv, Junchi Yan, Li Shang, Stephen M. Chu
Collaborative filtering (CF) is a popular technique in today's recommender systems, and matrix approximation-based CF methods have achieved great success in both rating prediction and top-N recommendation tasks.
1 code implementation • 4 Sep 2018 • Chao Chen, Boyuan Jiang, Xinyu Jin
Unlike the existing parameter transfer approaches, which incorporate the source model information into the target by regularizing the di erence between the source and target domain parameters, an intuitively appealing projective-model is proposed to bridge the source and target model parameters.
1 code implementation • 28 Aug 2018 • Chao Chen, Zhihong Chen, Boyuan Jiang, Xinyu Jin
Recently, considerable effort has been devoted to deep domain adaptation in computer vision and machine learning communities.
no code implementations • 27 Jun 2018 • Chao Chen, Xiuyan Ni, Qinxun Bai, Yusu Wang
In particular, our measurement of topological complexity incorporates the importance of topological features (e. g., connected components, handles, and so on) in a meaningful manner, and provides a direct control over spurious topological structures.
no code implementations • 23 Dec 2017 • Chao Chen, Xiao Lin, Gabriel Terejanu
In this study, we propose an approximate estimation of the weights uncertainty using Ensemble Kalman Filter, which is easily scalable to a large number of weights.
no code implementations • NeurIPS 2017 • Dongsheng Li, Chao Chen, Wei Liu, Tun Lu, Ning Gu, Stephen Chu
However, our studies show that submatrices with different ranks could coexist in the same user-item rating matrix, so that approximations with fixed ranks cannot perfectly describe the internal structures of the rating matrix, therefore leading to inferior recommendation accuracy.
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no code implementations • 31 Oct 2017 • Changzhe Jiao, Chao Chen, Ronald G. McGarvey, Stephanie Bohlman, Licheng Jiao, Alina Zare
The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented.
no code implementations • ICML 2017 • Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen
Clustering data with both continuous and discrete attributes is a challenging task.
2 code implementations • 28 Dec 2016 • Chao Chen, Alina Zare, Huy Trinh, Gbeng Omotara, J. Tory Cobb, Timotius Lagaunne
Topic models (e. g., pLSA, LDA, sLDA) have been widely used for segmenting imagery.
2 code implementations • 9 Nov 2015 • Chao Chen, Alina Zare, J. Tory Cobb
Topic models (e. g., pLSA, LDA, SLDA) have been widely used for segmenting imagery.
no code implementations • NeurIPS 2014 • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao
Though the mode finding problem is generally intractable in high dimensions, this paper unveils that, if the distribution can be approximated well by a tree graphical model, mode characterization is significantly easier.