Search Results for author: Chen Zhao

Found 44 papers, 16 papers with code

Sparse-to-Dense Depth Completion Revisited: Sampling Strategy and Graph Construction

no code implementations ECCV 2020 Xin Xiong, Haipeng Xiong, Ke Xian, Chen Zhao, Zhiguo Cao, Xin Li

Depth completion is a widely studied problem of predicting a dense depth map from a sparse set of measurements and a single RGB image.

Depth Completion graph construction

What’s in a Name? Answer Equivalence For Open-Domain Question Answering

1 code implementation EMNLP 2021 Chenglei Si, Chen Zhao, Jordan Boyd-Graber

We incorporate answers for two settings: evaluation with additional answers and model training with equivalent answers.

Open-Domain Question Answering

Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation

1 code implementation EMNLP 2021 Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III

This paper investigates whether models can learn to find evidence from a large corpus, with only distant supervision from answer labels for model training, thereby generating no additional annotation cost.

Open-Domain Question Answering

MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions

1 code implementation1 Dec 2021 Mattia Soldan, Alejandro Pardo, Juan León Alcázar, Fabian Caba Heilbron, Chen Zhao, Silvio Giancola, Bernard Ghanem

The recent and increasing interest in video-language research has driven the development of large-scale datasets that enable data-intensive machine learning techniques.

Moment Retrieval Natural Language Moment Retrieval

Spatial-temporal V-Net for automatic segmentation and quantification of right ventricles in gated myocardial perfusion SPECT images

no code implementations11 Oct 2021 Chen Zhao, Shi Shi, Zhuo He, Cheng Wang, Zhongqiang Zhao, Xinli Li, Yanli Zhou, Weihua Zhou

By integrating the spatial features from each cardiac frame of gated MPS and the temporal features from the sequential cardiac frames of the gated MPS, we develop a Spatial-Temporal V-Net (S-T-V-Net) for automatic extraction of RV endocardial and epicardial contours.

Automatic Identification of the End-Diastolic and End-Systolic Cardiac Frames from Invasive Coronary Angiography Videos

no code implementations6 Oct 2021 Yinghui Meng, Minghao Dong, Xumin Dai, Haipeng Tang, Chen Zhao, Jingfeng Jiang, Shun Xu, Ying Zhou, Fubao Zhu1, Zhihui Xu, Weihua Zhou

More specifically, a detection algorithm is first used to detect the key points of coronary arteries, and then an optical flow method is employed to track the trajectories of the selected key points.

Optical Flow Estimation

What's in a Name? Answer Equivalence For Open-Domain Question Answering

1 code implementation11 Sep 2021 Chenglei Si, Chen Zhao, Jordan Boyd-Graber

We incorporate answers for two settings: evaluation with additional answers and model training with equivalent answers.

Open-Domain Question Answering

Fairness-Aware Online Meta-learning

no code implementations21 Aug 2021 Chen Zhao, Feng Chen, Bhavani Thuraisingham

To overcome such issues and bridge the gap, in this paper for the first time we proposed a novel online meta-learning algorithm, namely FFML, which is under the setting of unfairness prevention.

Fairness Meta-Learning

FedSup: A Communication-Efficient Federated Learning Fatigue Driving Behaviors Supervision Framework

no code implementations25 Apr 2021 Chen Zhao, Zhipeng Gao, Qian Wang, Kaile Xiao, Zijia Mo, M. Jamal Deen

With the proliferation of edge smart devices and the Internet of Vehicles (IoV) technologies, intelligent fatigue detection has become one of the most-used methods in our daily driving.

Federated Learning

Complex Factoid Question Answering with a Free-Text Knowledge Graph

no code implementations23 Mar 2021 Chen Zhao, Chenyan Xiong, Xin Qian, Jordan Boyd-Graber

DELFT's advantage comes from both the high coverage of its free-text knowledge graph-more than double that of dbpedia relations-and the novel graph neural network which reasons on the rich but noisy free-text evidence.

Graph Question Answering Question Answering +1

A Deep Learning-based Method to Extract Lumen and Media-Adventitia in Intravascular Ultrasound Images

no code implementations21 Feb 2021 Fubao Zhu, Zhengyuan Gao, Chen Zhao, Hanlei Zhu, Yong Dong, Jingfeng Jiang, Neng Dai, Weihua Zhou

In this paper, we aim to develop a deep learning-based method using an encoder-decoder deep architecture to automatically extract both lumen and MA border.

A Deep Learning-Based Approach to Extracting Periosteal and Endosteal Contours of Proximal Femur in Quantitative CT Images

no code implementations3 Feb 2021 Yu Deng, Ling Wang, Chen Zhao, Shaojie Tang, Xiaoguang Cheng, Hong-Wen Deng, Weihua Zhou

In this study, we proposed an approach based on deep learning for the automatic extraction of the periosteal and endosteal contours of proximal femur in order to differentiate cortical and trabecular bone compartments.

Interactive Segmentation

Analyzing the barren plateau phenomenon in training quantum neural networks with the ZX-calculus

no code implementations3 Feb 2021 Chen Zhao, Xiao-Shan Gao

In this paper, we propose a general scheme to analyze the gradient vanishing phenomenon, also known as the barren plateau phenomenon, in training quantum neural networks with the ZX-calculus.

A new approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms

no code implementations25 Jan 2021 Chen Zhao, Haipeng Tang, Daniel McGonigle, Zhuo He, Chaoyang Zhang, Yu-Ping Wang, Hong-Wen Deng, Robert Bober, Weihua Zhou

We aim to develop an automatic algorithm by deep learning to extract coronary arteries from ICAs. In this study, a multi-input and multi-scale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation.

Progressive Correspondence Pruning by Consensus Learning

no code implementations ICCV 2021 Chen Zhao, Yixiao Ge, Feng Zhu, Rui Zhao, Hongsheng Li, Mathieu Salzmann

Correspondence selection aims to correctly select the consistent matches (inliers) from an initial set of putative correspondences.

Denoising Pose Estimation

Wetting equilibrium in a rectangular channel

no code implementations3 Dec 2020 Tian Yu, Qicheng Sun, Chen Zhao, Jiajia Zhou, Masao Doi

When a capillary channel with corners is wetted by a fluid, there are regions where the fluid fills the whole cross-section and regions where only the corners are filled by the fluid.

Soft Condensed Matter

A Nested Bi-level Optimization Framework for Robust Few Shot Learning

no code implementations13 Nov 2020 KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Rishabh Iyer, Feng Chen

Model-Agnostic Meta-Learning (MAML), a popular gradient-based meta-learning framework, assumes that the contribution of each task or instance to the meta-learner is equal.

Few-Shot Learning

A Primal-Dual Subgradient Approachfor Fair Meta Learning

1 code implementation26 Sep 2020 Chen Zhao, Feng Chen, Zhuoyi Wang, Latifur Khan

In this work, we propose a Primal-Dual Fair Meta-learning framework, namely PDFM, which learns to train fair machine learning models using only a few examples based on data from related tasks.

Fairness Few-Shot Learning

Unfairness Discovery and Prevention For Few-Shot Regression

no code implementations23 Sep 2020 Chen Zhao, Feng Chen

In this work, we first discover discrimination from data using a causal Bayesian knowledge graph which not only demonstrates the dependency of the protected variable on target but also indicates causal effects between all variables.

Fairness Meta-Learning

Fair Meta-Learning For Few-Shot Classification

no code implementations23 Sep 2020 Chen Zhao, Changbin Li, Jincheng Li, Feng Chen

Artificial intelligence nowadays plays an increasingly prominent role in our life since decisions that were once made by humans are now delegated to automated systems.

Fairness General Classification +1

Rank-Based Multi-task Learning for Fair Regression

no code implementations23 Sep 2020 Chen Zhao, Feng Chen

In this work, we develop a novel fairness learning approach for multi-task regression models based on a biased training dataset, using a popular rank-based non-parametric independence test, i. e., Mann Whitney U statistic, for measuring the dependency between target variable and protected variables.

Fairness Multi-Task Learning

A Novel Method for ECG Signal Classification via One-Dimensional Convolutional Neural Network

no code implementations20 Jun 2020 Xuan Hua, Jungang Han, Chen Zhao, Haipeng Tang, Zhuo He, Jinshan Tang, Qing-Hui Chen, Shaojie Tang, Weihua Zhou

This paper presents an end-to-end ECG signal classification method based on a novel segmentation strategy via 1D Convolutional Neural Networks (CNN) to aid the classification of ECG signals.

General Classification

A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images

no code implementations9 Jun 2020 Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou

During the experiments for the entire cohort then for male and female subjects separately, 90% of the subjects were used in 10-fold cross-validation for training and internal validation, and to select the optimal parameters of the proposed models; the rest of the subjects were used to evaluate the performance of models.

Semantic Segmentation

QDNN: DNN with Quantum Neural Network Layers

1 code implementation29 Dec 2019 Chen Zhao, Xiao-Shan Gao

In this paper, we introduce a quantum extension of classical DNN, QDNN.

Image Classification

Learning Semantic Neural Tree for Human Parsing

no code implementations ECCV 2020 Ruyi Ji, Dawei Du, Libo Zhang, Longyin Wen, Yanjun Wu, Chen Zhao, Feiyue Huang, Siwei Lyu

In this paper, we design a novel semantic neural tree for human parsing, which uses a tree architecture to encode physiological structure of human body, and designs a coarse to fine process in a cascade manner to generate accurate results.

Human Parsing Semantic Segmentation

G-TAD: Sub-Graph Localization for Temporal Action Detection

4 code implementations CVPR 2020 Mengmeng Xu, Chen Zhao, David S. Rojas, Ali Thabet, Bernard Ghanem

In this work, we propose a graph convolutional network (GCN) model to adaptively incorporate multi-level semantic context into video features and cast temporal action detection as a sub-graph localization problem.

Graph Convolutional Network Temporal Action Localization

Rotation Invariant Point Cloud Classification: Where Local Geometry Meets Global Topology

1 code implementation1 Nov 2019 Chen Zhao, Jiaqi Yang, Xin Xiong, Angfan Zhu, Zhiguo Cao, Xin Li

To the best of our knowledge, this work is the first principled approach toward adaptively combining global and local information under the context of RI point cloud analysis.

General Classification Point Cloud Classification

Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization

2 code implementations CVPR 2020 Ruyi Ji, Longyin Wen, Libo Zhang, Dawei Du, Yanjun Wu, Chen Zhao, Xianglong Liu, Feiyue Huang

Specifically, we incorporate convolutional operations along edges of the tree structure, and use the routing functions in each node to determine the root-to-leaf computational paths within the tree.

Fine-Grained Image Classification Fine-Grained Visual Categorization

Iterative Clustering with Game-Theoretic Matching for Robust Multi-consistency Correspondence

no code implementations3 Sep 2019 Chen Zhao, Jiaqi Yang, Ke Xian, Zhiguo Cao, Xin Li

Matching corresponding features between two images is a fundamental task to computer vision with numerous applications in object recognition, robotics, and 3D reconstruction.

3D Reconstruction Object Recognition

Comparative evaluation of 2D feature correspondence selection algorithms

1 code implementation30 Apr 2019 Chen Zhao, Jiaqi Yang, Yang Xiao, Zhiguo Cao

Correspondence selection aiming at seeking correct feature correspondences from raw feature matches is pivotal for a number of feature-matching-based tasks.

Learning to Fuse Local Geometric Features for 3D Rigid Data Matching

no code implementations27 Apr 2019 Jiaqi Yang, Chen Zhao, Ke Xian, Angfan Zhu, Zhiguo Cao

This paper presents a simple yet very effective data-driven approach to fuse both low-level and high-level local geometric features for 3D rigid data matching.

ThumbNet: One Thumbnail Image Contains All You Need for Recognition

no code implementations10 Apr 2019 Chen Zhao, Bernard Ghanem

Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources.

NM-Net: Mining Reliable Neighbors for Robust Feature Correspondences

1 code implementation CVPR 2019 Chen Zhao, Zhiguo Cao, Chi Li, Xin Li, Jiaqi Yang

Feature correspondence selection is pivotal to many feature-matching based tasks in computer vision.

A dataset and baselines for sequential open-domain question answering

no code implementations EMNLP 2018 Ahmed Elgohary, Chen Zhao, Jordan Boyd-Graber

Previous work on question-answering systems mainly focuses on answering individual questions, assuming they are independent and devoid of context.

Information Retrieval Open-Domain Question Answering +1

LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning

1 code implementation9 May 2016 Chengxi Ye, Chen Zhao, Yezhou Yang, Cornelia Fermuller, Yiannis Aloimonos

LightNet is a lightweight, versatile and purely Matlab-based deep learning framework.

Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization

no code implementations30 Apr 2014 Jian Zhang, Chen Zhao, Debin Zhao, Wen Gao

From many fewer acquired measurements than suggested by the Nyquist sampling theory, compressive sensing (CS) theory demonstrates that, a signal can be reconstructed with high probability when it exhibits sparsity in some domain.

Compressive Sensing

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