Search Results for author: Xin Yang

Found 79 papers, 21 papers with code

Self-supervised Representation Learning for Trip Recommendation

no code implementations2 Sep 2021 Qiang Gao, Wei Wang, Kunpeng Zhang, Xin Yang, Congcong Miao

Although recent deep recursive models (e. g., RNN) are capable of alleviating these concerns, existing solutions hardly recognize the practical reality, such as the diversity of tourist demands, uncertainties in the trip generation, and the complex visiting preference.

Contrastive Learning Representation Learning

WRICNet:A Weighted Rich-scale Inception Coder Network for Multi-Resolution Remote Sensing Image Change Detection

no code implementations18 Aug 2021 Yu Jiang, Lei Hu, Yongmei Zhang, Xin Yang

With the purpose of improving change detection effectiveness of the model in the multi-resolution data set, a weighted rich-scale inception coder network (WRICNet) is proposed in this article, which can make a great fusion of shallow multi-scale features, and deep multi-scale features.

Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking

no code implementations10 Aug 2021 Jiqing Zhang, Kai Zhao, Bo Dong, Yingkai Fu, Yuxin Wang, Xin Yang, BaoCai Yin

Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking.

Visual Object Tracking

Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?

1 code implementation1 Aug 2021 Zhoubo Xu, Puqing Chen, Romain Raveaux, Xin Yang, Huadong Liu

Graph matching is an important problem that has received widespread attention, especially in the field of computer vision.

Graph Matching

Prior-Induced Information Alignment for Image Matting

no code implementations28 Jun 2021 Yuhao Liu, Jiake Xie, Yu Qiao, Yong Tang and, Xin Yang

Image matting is an ill-posed problem that aims to estimate the opacity of foreground pixels in an image.

Image Matting

Depth-Aware Mirror Segmentation

no code implementations CVPR 2021 Haiyang Mei, Bo Dong, Wen Dong, Pieter Peers, Xin Yang, Qiang Zhang, Xiaopeng Wei

To exploit depth information in mirror segmentation, we first construct a large-scale RGB-D mirror segmentation dataset, which we subsequently employ to train a novel depth-aware mirror segmentation framework.

Feature-Level Collaboration: Joint Unsupervised Learning of Optical Flow, Stereo Depth and Camera Motion

no code implementations CVPR 2021 Cheng Chi, Qingjie Wang, Tianyu Hao, Peng Guo, Xin Yang

In this paper, we show that effective feature-level collaboration of the networks for the three respective tasks could achieve much greater performance improvement for all three tasks than only loss-level joint optimization.

Depth And Camera Motion Motion Estimation +4

Joint Landmark and Structure Learning for Automatic Evaluation of Developmental Dysplasia of the Hip

no code implementations10 Jun 2021 Xindi Hu, LiMin Wang, Xin Yang, Xu Zhou, Wufeng Xue, Yan Cao, Shengfeng Liu, Yuhao Huang, Shuangping Guo, Ning Shang, Dong Ni, Ning Gu

In this study, we propose a multi-task framework to learn the relationships among landmarks and structures jointly and automatically evaluate DDH.

Vertical Federated Learning without Revealing Intersection Membership

no code implementations10 Jun 2021 Jiankai Sun, Xin Yang, Yuanshun Yao, Aonan Zhang, Weihao Gao, Junyuan Xie, Chong Wang

In this paper, we propose a vFL framework based on Private Set Union (PSU) that allows each party to keep sensitive membership information to itself.

Federated Learning

Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary Learning

no code implementations7 Jun 2021 Xin Yang, Ning Zhang, Donglin Wang

Fourth, we generate three corresponding masks based on the 20 selected ROIs from group ICA, the 20 ROIs selected from dictionary learning, and the 40 combined ROIs selected from both.

Dictionary Learning

Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images

no code implementations19 May 2021 Guang-Quan Zhou, Juzheng Miao, Xin Yang, Rui Li, En-Ze Huo, Wenlong Shi, Yuhao Huang, Jikuan Qian, Chaoyu Chen, Dong Ni

Our proposed framework is general and shows the potential to improve the efficiency of anatomical landmark detection.

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis

no code implementations11 May 2021 Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang

Nevertheless, training analysis of neural networks in FL is non-trivial for two reasons: first, the objective loss function we are optimizing is non-smooth and non-convex, and second, we are even not updating in the gradient direction.

Federated Learning

Camouflaged Object Segmentation with Distraction Mining

no code implementations CVPR 2021 Haiyang Mei, Ge-Peng Ji, Ziqi Wei, Xin Yang, Xiaopeng Wei, Deng-Ping Fan

In this paper, we strive to embrace challenges towards effective and efficient COS. To this end, we develop a bio-inspired framework, termed Positioning and Focus Network (PFNet), which mimics the process of predation in nature.

Camouflaged Object Segmentation Semantic Segmentation

A Two-Stage Attentive Network for Single Image Super-Resolution

1 code implementation21 Apr 2021 Jiqing Zhang, Chengjiang Long, Yuxin Wang, Haiyin Piao, Haiyang Mei, Xin Yang, BaoCai Yin

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and contribute remarkable progress.

Image Reconstruction Image Super-Resolution

Smart Scribbles for Image Mating

no code implementations31 Mar 2021 Xin Yang, Yu Qiao, Shaozhe Chen, Shengfeng He, BaoCai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau

Image matting is an ill-posed problem that usually requires additional user input, such as trimaps or scribbles.

Image Matting

Label Leakage and Protection in Two-party Split Learning

2 code implementations17 Feb 2021 Oscar Li, Jiankai Sun, Xin Yang, Weihao Gao, Hongyi Zhang, Junyuan Xie, Virginia Smith, Chong Wang

We first show that, norm attack, a simple method that uses the norm of the communicated gradients between the parties, can largely reveal the ground-truth labels from the participants.

Federated Learning

Automatic Comic Generation with Stylistic Multi-page Layouts and Emotion-driven Text Balloon Generation

no code implementations26 Jan 2021 Xin Yang, Zongliang Ma, Letian Yu, Ying Cao, BaoCai Yin, Xiaopeng Wei, Qiang Zhang, Rynson W. H. Lau

Finally, as opposed to using the same type of balloon as in previous works, we propose an emotion-aware balloon generation method to create different types of word balloons by analyzing the emotion of subtitles and audios.

CPT: Efficient Deep Neural Network Training via Cyclic Precision

1 code implementation ICLR 2021 Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin

In this paper, we attempt to explore low-precision training from a new perspective as inspired by recent findings in understanding DNN training: we conjecture that DNNs' precision might have a similar effect as the learning rate during DNN training, and advocate dynamic precision along the training trajectory for further boosting the time/energy efficiency of DNN training.

Language Modelling

Multi-scale Information Assembly for Image Matting

no code implementations7 Jan 2021 Yu Qiao, Yuhao Liu, Qiang Zhu, Xin Yang, Yuxin Wang, Qiang Zhang, Xiaopeng Wei

Image matting is a long-standing problem in computer graphics and vision, mostly identified as the accurate estimation of the foreground in input images.

Image Matting

DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets

no code implementations13 Oct 2020 Shujun Wang, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng

Our DoFE framework dynamically enriches the image features with additional domain prior knowledge learned from multi-source domains to make the semantic features more discriminative.

Domain Generalization Semantic Segmentation

Weakly-supervised Salient Instance Detection

no code implementations29 Sep 2020 Xin Tian, Ke Xu, Xin Yang, Bao-Cai Yin, Rynson W. H. Lau

Inspired by this insight, we propose to use class and subitizing labels as weak supervision for the SID problem.

Boundary Detection Object Localization +1

Style-invariant Cardiac Image Segmentation with Test-time Augmentation

no code implementations24 Sep 2020 Xiaoqiong Huang, Zejian Chen, Xin Yang, Zhendong Liu, Yuxin Zou, Mingyuan Luo, Wufeng Xue, Dong Ni

Based on the zero-shot style transfer to remove appearance shift and test-time augmentation to explore diverse underlying anatomy, our proposed method is effective in combating the appearance shift.

Cardiac Segmentation Semantic Segmentation +1

Designing Neural Networks for Real-Time Systems

no code implementations26 Aug 2020 Hammond Pearce, Xin Yang, Partha S. Roop, Marc Katzef, Tórur Biskopstø Strøm

This issue stems largely from the implementation strategies used within common neural network frameworks -- their underlying source code is often simply unsuitable for formal techniques such as static timing analysis.

Computer-aided Tumor Diagnosis in Automated Breast Ultrasound using 3D Detection Network

no code implementations31 Jul 2020 Junxiong Yu, Chaoyu Chen, Xin Yang, Yi Wang, Dan Yan, Jianxing Zhang, Dong Ni

The efficacy of our network is verified from a collected dataset of 418 patients with 145 benign tumors and 273 malignant tumors.

Breast Cancer Detection Classification +1

TENet: Triple Excitation Network for Video Salient Object Detection

no code implementations ECCV 2020 Sucheng Ren, Chu Han, Xin Yang, Guoqiang Han, Shengfeng He

In this paper, we propose a simple yet effective approach, named Triple Excitation Network, to reinforce the training of video salient object detection (VSOD) from three aspects, spatial, temporal, and online excitations.

Curriculum Learning Salient Object Detection +1

Hybrid Attention for Automatic Segmentation of Whole Fetal Head in Prenatal Ultrasound Volumes

1 code implementation28 Apr 2020 Xin Yang, Xu Wang, Yi Wang, Haoran Dou, Shengli Li, Huaxuan Wen, Yi Lin, Pheng-Ann Heng, Dong Ni

In this paper, we propose the first fully-automated solution to segment the whole fetal head in US volumes.

A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI

2 code implementations27 Apr 2020 Haoran Dou, Davood Karimi, Caitlin K. Rollins, Cynthia M. Ortinau, Lana Vasung, Clemente Velasco-Annis, Abdelhakim Ouaalam, Xin Yang, Dong Ni, Ali Gholipour

Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation.

Sketching Transformed Matrices with Applications to Natural Language Processing

no code implementations23 Feb 2020 Yingyu Liang, Zhao Song, Mengdi Wang, Lin F. Yang, Xin Yang

We show that our approach obtains small error and is efficient in both space and time.

One-Shot Imitation Filming of Human Motion Videos

no code implementations23 Dec 2019 Chong Huang, Yuanjie Dang, Peng Chen, Xin Yang, Kwang-Ting, Cheng

Imitation learning has been applied to mimic the operation of a human cameraman in several autonomous cinematography systems.

Imitation Learning Style Transfer

Adaptive Densely Connected Super-Resolution Reconstruction

1 code implementation17 Dec 2019 Tangxin Xie, Xin Yang, Yu Jia, Chen Zhu, Xiaochuan Li

For a better performance in single image super-resolution(SISR), we present an image super-resolution algorithm based on adaptive dense connection (ADCSR).

Image Super-Resolution SSIM

Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound

1 code implementation10 Oct 2019 Haoran Dou, Xin Yang, Jikuan Qian, Wufeng Xue, Hao Qin, Xu Wang, Lequan Yu, Shujun Wang, Yi Xiong, Pheng-Ann Heng, Dong Ni

In this study, we propose a novel reinforcement learning (RL) framework to automatically localize fetal brain standard planes in 3D US.

Total Least Squares Regression in Input Sparsity Time

1 code implementation NeurIPS 2019 Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang

In the total least squares problem, one is given an $m \times n$ matrix $A$, and an $m \times d$ matrix $B$, and one seeks to "correct" both $A$ and $B$, obtaining matrices $\hat{A}$ and $\hat{B}$, so that there exists an $X$ satisfying the equation $\hat{A}X = \hat{B}$.

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

5 code implementations CVPR 2020 Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu

AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information.

DeepFake Detection Face Swapping

Joint Segmentation and Landmark Localization of Fetal Femur in Ultrasound Volumes

no code implementations31 Aug 2019 Xu Wang, Xin Yang, Haoran Dou, Shengli Li, Pheng-Ann Heng, Dong Ni

In this paper, we propose an effective framework for simultaneous segmentation and landmark localization in prenatal ultrasound volumes.

Urban flows prediction from spatial-temporal data using machine learning: A survey

no code implementations26 Aug 2019 Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, Junbo Zhang

Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc.

Transfer Learning

Where Is My Mirror?

1 code implementation ICCV 2019 Xin Yang, Haiyang Mei, Ke Xu, Xiaopeng Wei, Bao-Cai Yin, Rynson W. H. Lau

To the best of our knowledge, this is the first work to address the mirror segmentation problem with a computational approach.

DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors

no code implementations23 Aug 2019 Xin Yang, Haiyang Mei, Jiqing Zhang, Ke Xu, Bao-Cai Yin, Qiang Zhang, Xiaopeng Wei

Recently, single-image super-resolution has made great progress owing to the development of deep convolutional neural networks (CNNs).

Image Super-Resolution

Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images

no code implementations22 Aug 2019 Jiexiang Wang, Cheng Bian, Meng Li, Xin Yang, Kai Ma, Wenao Ma, Jin Yuan, Xinghao Ding, Yefeng Zheng

Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases.

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

1 code implementation3 Jul 2019 Yi Wang, Haoran Dou, Xiao-Wei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin, Pheng-Ann Heng, Tianfu Wang, Dong Ni

Our attention module utilizes the attention mechanism to selectively leverage the multilevel features integrated from different layers to refine the features at each individual layer, suppressing the non-prostate noise at shallow layers of the CNN and increasing more prostate details into features at deep layers.

Medical Image Segmentation

Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation

1 code implementation26 Jun 2019 Shujun Wang, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng

The cross-domain discrepancy (domain shift) hinders the generalization of deep neural networks to work on different domain datasets. In this work, we present an unsupervised domain adaptation framework, called Boundary and Entropy-driven Adversarial Learning (BEAL), to improve the OD and OC segmentation performance, especially on the ambiguous boundary regions.

Semantic Segmentation Unsupervised Domain Adaptation

Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound

no code implementations9 Jun 2019 Zhao Song, Xin Yang

We improve the over-parametrization size over two beautiful results [Li and Liang' 2018] and [Du, Zhai, Poczos and Singh' 2019] in deep learning theory.

Learning Theory

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset

2 code implementations CVPR 2019 Tianyu Wang, Xin Yang, Ke Xu, Shaozhe Chen, Qiang Zhang, Rynson Lau

Second, to better cover the stochastic distribution of real rain streaks, we propose a novel SPatial Attentive Network (SPANet) to remove rain streaks in a local-to-global manner.

Single Image Deraining

Exposing GAN-synthesized Faces Using Landmark Locations

no code implementations30 Mar 2019 Xin Yang, Yuezun Li, Honggang Qi, Siwei Lyu

Generative adversary networks (GANs) have recently led to highly realistic image synthesis results.

General Classification Image Generation

Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image

no code implementations CVPR 2019 Xiaoguang Han, Zhaoxuan Zhang, Dong Du, Mingdai Yang, Jingming Yu, Pan Pan, Xin Yang, Ligang Liu, Zixiang Xiong, Shuguang Cui

Given a single depth image, our method first goes through the 3D volume branch to obtain a volumetric scene reconstruction as a guide to the next view inpainting step, which attempts to make up the missing information; the third step involves projecting the volume under the same view of the input, concatenating them to complete the current view depth, and integrating all depth into the point cloud.

Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation

no code implementations20 Feb 2019 Shujun Wang, Lequan Yu, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng

In this paper, we present a novel patchbased Output Space Adversarial Learning framework (pOSAL) to jointly and robustly segment the OD and OC from different fundus image datasets.

Unsupervised Domain Adaptation

Semi-supervised mp-MRI Data Synthesis with StitchLayer and Auxiliary Distance Maximization

no code implementations17 Dec 2018 Zhiwei Wang, Yi Lin, Kwang-Ting Cheng, Xin Yang

Experimental results show that our method can effectively synthesize a large variety of mpMRI images which contain meaningful CS PCa lesions, display a good visual quality and have the correct paired relationship.

Synthesizing Multi-Parameter Magnetic Resonance Imaging (Mp-Mri) Data

Deep Hierarchical Machine: a Flexible Divide-and-Conquer Architecture

no code implementations3 Dec 2018 Shichao Li, Xin Yang, Tim Cheng

We propose Deep Hierarchical Machine (DHM), a model inspired from the divide-and-conquer strategy while emphasizing representation learning ability and flexibility.

Face Alignment General Classification +2

Active Matting

no code implementations NeurIPS 2018 Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin Yin, Rynson Lau

Our aim is to discover the most informative sequence of regions for user input in order to produce a good alpha matte with minimum labeling efforts.

Image Matting

Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance

1 code implementation4 Nov 2018 Zechun Liu, Wenhan Luo, Baoyuan Wu, Xin Yang, Wei Liu, Kwang-Ting Cheng

To address the training difficulty, we propose a training algorithm using a tighter approximation to the derivative of the sign function, a magnitude-aware gradient for weight updating, a better initialization method, and a two-step scheme for training a deep network.

Depth Estimation

Exposing Deep Fakes Using Inconsistent Head Poses

1 code implementation1 Nov 2018 Xin Yang, Yuezun Li, Siwei Lyu

In this paper, we propose a new method to expose AI-generated fake face images or videos (commonly known as the Deep Fakes).

General Classification

Tool Breakage Detection using Deep Learning

no code implementations16 Aug 2018 Guang Li, Xin Yang, DuanBing Chen, Anxing Song, Yuke Fang, Junlin Zhou

In this work, we use the spindle current approach to detect the breakage of machine tools, which has the high performance of real-time monitoring, low cost, and easy to install.

Active Object Reconstruction Using a Guided View Planner

no code implementations8 May 2018 Xin Yang, Yuanbo Wang, Yaru Wang, Bao-Cai Yin, Qiang Zhang, Xiaopeng Wei, Hongbo Fu

Inspired by the recent advance of image-based object reconstruction using deep learning, we present an active reconstruction model using a guided view planner.

Object Reconstruction

Neural Compatibility Modeling with Attentive Knowledge Distillation

no code implementations17 Apr 2018 Xuemeng Song, Fuli Feng, Xianjing Han, Xin Yang, Wei Liu, Liqiang Nie

Nevertheless, existing studies overlook the rich valuable knowledge (rules) accumulated in fashion domain, especially the rules regarding clothing matching.

Image Classification Knowledge Distillation +1

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI

1 code implementation Elsevier 2017 Xin Yang, Chaoyue Liu, Zhiwei Wang, Jun Yang, Hung Le Min, Liang Wang, Kwang-Ting (Tim) Cheng

Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions’ locations.

General Classification

Time-Space Tradeoffs for Learning from Small Test Spaces: Learning Low Degree Polynomial Functions

no code implementations8 Aug 2017 Paul Beame, Shayan Oveis Gharan, Xin Yang

We develop an extension of recently developed methods for obtaining time-space tradeoff lower bounds for problems of learning from random test samples to handle the situation where the space of tests is signficantly smaller than the space of inputs, a class of learning problems that is not handled by prior work.

Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets

2 code implementations2 Aug 2017 Lequan Yu, Jie-Zhi Cheng, Qi Dou, Xin Yang, Hao Chen, Jing Qin, Pheng-Ann Heng

Second, it avoids learning redundant feature maps by encouraging feature reuse and hence requires fewer parameters to achieve high performance, which is essential for medical applications with limited training data.

Fine-grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images

no code implementations6 Dec 2016 Xin Yang, Lequan Yu, Lingyun Wu, Yi Wang, Dong Ni, Jing Qin, Pheng-Ann Heng

Additionally, our approach is general and can be extended to other medical image segmentation tasks, where boundary incompleteness is one of the main challenges.

Medical Image Segmentation

Concept based Attention

no code implementations11 May 2016 Jie You, Xin Yang, Matthias Hub

Attention endows animals an ability to concentrate on the most relevant information among a deluge of distractors at any given time, either through volitionally 'top-down' biasing, or driven by automatically 'bottom-up' saliency of stimuli, in favour of advantageous competition in neural modulations for information processing.

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