Search Results for author: Jing Qin

Found 67 papers, 32 papers with code

Single-View View Synthesis with Self-Rectified Pseudo-Stereo

no code implementations19 Apr 2023 Yang Zhou, Hanjie Wu, Wenxi Liu, Zheng Xiong, Jing Qin, Shengfeng He

In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction.

3D Reconstruction Novel View Synthesis

Human Motion Detection Based on Dual-Graph and Weighted Nuclear Norm Regularizations

no code implementations10 Apr 2023 Jing Qin, Biyun Xie

In the meanwhile, geometry-based regularizations, such as graph regularizations, can be imposed on the foreground.

Motion Detection Moving Object Detection +1

Federated Gradient Matching Pursuit

no code implementations20 Feb 2023 Halyun Jeong, Deanna Needell, Jing Qin

In particular, federated learning (FL) provides such a solution to learn a shared model while keeping training data at local clients.

Federated Learning Privacy Preserving

RainDiffusion: When Unsupervised Learning Meets Diffusion Models for Real-world Image Deraining

no code implementations23 Jan 2023 Mingqiang Wei, Yiyang Shen, Yongzhen Wang, Haoran Xie, Jing Qin, Fu Lee Wang

Before answering it, we observe two major obstacles of diffusion models in real-world image deraining: the need for paired training data and the limited utilization of multi-scale rain patterns.

Rain Removal Translation

ImLiDAR: Cross-Sensor Dynamic Message Propagation Network for 3D Object Detection

no code implementations17 Nov 2022 Yiyang Shen, Rongwei Yu, Peng Wu, Haoran Xie, Lina Gong, Jing Qin, Mingqiang Wei

We propose ImLiDAR, a new 3OD paradigm to narrow the cross-sensor discrepancies by progressively fusing the multi-scale features of camera Images and LiDAR point clouds.

3D Object Detection object-detection

UTOPIC: Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration

1 code implementation4 Aug 2022 Zhilei Chen, Honghua Chen, Lina Gong, Xuefeng Yan, Jun Wang, Yanwen Guo, Jing Qin, Mingqiang Wei

High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner.

Point Cloud Registration

CSDN: Cross-modal Shape-transfer Dual-refinement Network for Point Cloud Completion

no code implementations1 Aug 2022 Zhe Zhu, Liangliang Nan, Haoran Xie, Honghua Chen, Mingqiang Wei, Jun Wang, Jing Qin

The first module transfers the intrinsic shape characteristics from single images to guide the geometry generation of the missing regions of point clouds, in which we propose IPAdaIN to embed the global features of both the image and the partial point cloud into completion.

Point Cloud Completion

Editing Out-of-domain GAN Inversion via Differential Activations

1 code implementation17 Jul 2022 Haorui Song, Yong Du, Tianyi Xiang, Junyu Dong, Jing Qin, Shengfeng He

Consequently, in the decomposition phase, we further present a GAN prior based deghosting network for separating the final fine edited image from the coarse reconstruction.

Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift

1 code implementation2 Jul 2022 Wenao Ma, Cheng Chen, Shuang Zheng, Jing Qin, Huimao Zhang, Qi Dou

In this paper, we propose the first method to tackle label shift for medical image classification, which effectively adapt the model learned from a single training label distribution to arbitrary unknown test label distribution.

Image Classification Medical Diagnosis +2

A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos

1 code implementation1 Jul 2022 Zhi Lin, Junhao Lin, Lei Zhu, Huazhu Fu, Jing Qin, Liansheng Wang

Moreover, we learn video-level features to classify the breast lesions of the original video as benign or malignant lesions to further enhance the final breast lesion detection performance in ultrasound videos.

Lesion Classification Lesion Detection

Dynamic Message Propagation Network for RGB-D Salient Object Detection

no code implementations20 Jun 2022 Baian Chen, Zhilei Chen, Xiaowei Hu, Jun Xu, Haoran Xie, Mingqiang Wei, Jing Qin

This paper presents a novel deep neural network framework for RGB-D salient object detection by controlling the message passing between the RGB images and depth maps on the feature level and exploring the long-range semantic contexts and geometric information on both RGB and depth features to infer salient objects.

object-detection RGB-D Salient Object Detection +1

An Improved Normed-Deformable Convolution for Crowd Counting

1 code implementation16 Jun 2022 Xin Zhong, Zhaoyi Yan, Jing Qin, WangMeng Zuo, Weigang Lu

However, the heads are not uniformly covered by the sampling points in the deformable convolution, resulting in loss of head information.

Crowd Counting

XBound-Former: Toward Cross-scale Boundary Modeling in Transformers

1 code implementation2 Jun 2022 Jiacheng Wang, Fei Chen, Yuxi Ma, Liansheng Wang, Zhaodong Fei, Jianwei Shuai, Xiangdong Tang, Qichao Zhou, Jing Qin

Skin lesion segmentation from dermoscopy images is of great significance in the quantitative analysis of skin cancers, which is yet challenging even for dermatologists due to the inherent issues, i. e., considerable size, shape and color variation, and ambiguous boundaries.

Lesion Segmentation Skin Lesion Segmentation

UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning

1 code implementation4 May 2022 Yongzhen Wang, Xuefeng Yan, Fu Lee Wang, Haoran Xie, Wenhan Yang, Mingqiang Wei, Jing Qin

From a different yet new perspective, this paper explores contrastive learning with an adversarial training effort to leverage unpaired real-world hazy and clean images, thus bridging the gap between synthetic and real-world haze is avoided.

Contrastive Learning Image Dehazing

Robust Dual-Graph Regularized Moving Object Detection

no code implementations25 Apr 2022 Jing Qin, Ruilong Shen, Ruihan Zhu, Biyun Xie

In the meanwhile, sparsity or smoothness based regularizations, such as total variation and $\ell_1$, can be imposed on the foreground.

Moving Object Detection object-detection

Detail-recovery Image Deraining via Dual Sample-augmented Contrastive Learning

1 code implementation6 Apr 2022 Yiyang Shen, Mingqiang Wei, Sen Deng, Wenhan Yang, Yongzhen Wang, Xiao-Ping Zhang, Meng Wang, Jing Qin

To bridge the two domain gaps, we propose a semi-supervised detail-recovery image deraining network (Semi-DRDNet) with dual sample-augmented contrastive learning.

Contrastive Learning Rain Removal

Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution

1 code implementation CVPR 2022 Guangyuan Li, Jun Lv, Yapeng Tian, Qi Dou, Chengyan Wang, Chenliang Xu, Jing Qin

However, existing methods still have two shortcomings: (1) they neglect that the multi-contrast features at different scales contain different anatomical details and hence lack effective mechanisms to match and fuse these features for better reconstruction; and (2) they are still deficient in capturing long-range dependencies, which are essential for the regions with complicated anatomical structures.


Refine-Net: Normal Refinement Neural Network for Noisy Point Clouds

1 code implementation23 Mar 2022 Haoran Zhou, Honghua Chen, Yingkui Zhang, Mingqiang Wei, Haoran Xie, Jun Wang, Tong Lu, Jing Qin, Xiao-Ping Zhang

Differently, our network is designed to refine the initial normal of each point by extracting additional information from multiple feature representations.

GeoBi-GNN: Geometry-aware Bi-domain Mesh Denoising via Graph Neural Networks

1 code implementation Computer-Aided Design 2022 Yingkui Zhang, Guibao Shen, Qiong Wang, Yinling Qian, Mingqiang Wei, Jing Qin

For the first time, we optimize both positions and normals (i. e., dual domains) in a unified framework of GNN, and show the powerful inter-coordination between the dual domains.


Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images

1 code implementation CVPR 2022 Huisi Wu, Zhaoze Wang, Youyi Song, Lin Yang, Jing Qin

We study the semi-supervised learning problem, using a few labeled data and a large amount of unlabeled data to train the network, by developing a cross-patch dense contrastive learning framework, to segment cellular nuclei in histopathologic images.

Contrastive Learning Image Segmentation +1

Real-time landmark detection for precise endoscopic submucosal dissection via shape-aware relation network

1 code implementation8 Nov 2021 Jiacheng Wang, Yueming Jin, Shuntian Cai, Hongzhi Xu, Pheng-Ann Heng, Jing Qin, Liansheng Wang

Compared with existing solutions, which either neglect geometric relationships among targeting objects or capture the relationships by using complicated aggregation schemes, the proposed network is capable of achieving satisfactory accuracy while maintaining real-time performance by taking full advantage of the spatial relations among landmarks.

Multi-Task Learning

Boundary-aware Transformers for Skin Lesion Segmentation

1 code implementation8 Oct 2021 Jiacheng Wang, Lan Wei, Liansheng Wang, Qichao Zhou, Lei Zhu, Jing Qin

Skin lesion segmentation from dermoscopy images is of great importance for improving the quantitative analysis of skin cancer.

Inductive Bias Lesion Segmentation +1

T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis

no code implementations ICLR 2022 Minhao Liu, Ailing Zeng, Qiuxia Lai, Ruiyuan Gao, Min Li, Jing Qin, Qiang Xu

In this work, we propose a novel tree-structured wavelet neural network for time series signal analysis, namely T-WaveNet, by taking advantage of an inherent property of various types of signals, known as the dominant frequency range.

Activity Recognition Representation Learning +2

Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video

1 code implementation28 Sep 2021 Jiacheng Wang, Yueming Jin, Liansheng Wang, Shuntian Cai, Pheng-Ann Heng, Jing Qin

On the other hand, we develop an active global memory to gather the global semantic correlation in long temporal range to current one, in which we gather the most informative frames derived from model uncertainty and frame similarity.

Optical Flow Estimation

Reducing Spatial Labeling Redundancy for Semi-supervised Crowd Counting

no code implementations6 Aug 2021 Yongtuo Liu, Sucheng Ren, Liangyu Chai, Hanjie Wu, Jing Qin, Dan Xu, Shengfeng He

In this way, we can transfer the original spatial labeling redundancy caused by individual similarities to effective supervision signals on the unlabeled regions.

Crowd Counting

From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data

1 code implementation6 Aug 2021 Ye Liu, Lei Zhu, Shunda Pei, Huazhu Fu, Jing Qin, Qing Zhang, Liang Wan, Wei Feng

Our DID-Net predicts the three component maps by progressively integrating features across scales, and refines each map by passing an independent refinement network.

Image Dehazing Single Image Dehazing

Active-set algorithms based statistical inference for shape-restricted generalized additive Cox regression models

no code implementations29 Jun 2021 Geng Deng, Guangning Xu, Qiang Fu, Xindong Wang, Jing Qin

In this paper, we introduce the shape-restricted inference to the celebrated Cox regression model (SR-Cox), in which the covariate response is modeled as shape-restricted additive functions.


Direction-aware Feature-level Frequency Decomposition for Single Image Deraining

no code implementations15 Jun 2021 Sen Deng, Yidan Feng, Mingqiang Wei, Haoran Xie, Yiping Chen, Jonathan Li, Xiao-Ping Zhang, Jing Qin

Second, we further establish communication channels between low-frequency maps and high-frequency maps to interactively capture structures from high-frequency maps and add them back to low-frequency maps and, simultaneously, extract details from low-frequency maps and send them back to high-frequency maps, thereby removing rain streaks while preserving more delicate features in the input image.

Single Image Deraining

Relational Graph Neural Network Design via Progressive Neural Architecture Search

no code implementations30 May 2021 Ailing Zeng, Minhao Liu, Zhiwei Liu, Ruiyuan Gao, Jing Qin, Qiang Xu

We propose a novel solution to addressing a long-standing dilemma in the representation learning of graph neural networks (GNNs): how to effectively capture and represent useful information embedded in long-distance nodes to improve the performance of nodes with low homophily without leading to performance degradation in nodes with high homophily.

Neural Architecture Search Node Classification +1

Triple-cooperative Video Shadow Detection

1 code implementation CVPR 2021 Zhihao Chen, Liang Wan, Lei Zhu, Jia Shen, Huazhu Fu, Wennan Liu, Jing Qin

The bottleneck is the lack of a well-established dataset with high-quality annotations for video shadow detection.

Saliency Detection Semantic Segmentation +3

Domain Adaptive Robotic Gesture Recognition with Unsupervised Kinematic-Visual Data Alignment

no code implementations6 Mar 2021 Xueying Shi, Yueming Jin, Qi Dou, Jing Qin, Pheng-Ann Heng

In this paper, we propose a novel unsupervised domain adaptation framework which can simultaneously transfer multi-modality knowledge, i. e., both kinematic and visual data, from simulator to real robot.

Gesture Recognition Surgical Gesture Recognition +1

Collaborative and Adversarial Learning of Focused and Dispersive Representations for Semi-Supervised Polyp Segmentation

no code implementations ICCV 2021 Huisi Wu, Guilian Chen, Zhenkun Wen, Jing Qin

In this paper, we present a novel semi-supervised polyp segmentation via collaborative and adversarial learning of focused and dispersive representations learning model, where focused and dispersive extraction module are used to deal with the diversity of location and shape of polyps.

Semantic Segmentation

Research Progress of News Recommendation Methods

no code implementations4 Dec 2020 Jing Qin

News recommendation systems were the earliest research field regarding recommendation systems, and were also the earliest recommendation field to apply the collaborative filtering method.

Collaborative Filtering Knowledge Graphs +2

MBA-RainGAN: Multi-branch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images

no code implementations21 May 2020 Yiyang Shen, Yidan Feng, Sen Deng, Dong Liang, Jing Qin, Haoran Xie, Mingqiang Wei

We observe three intriguing phenomenons that, 1) rain is a mixture of raindrops, rain streaks and rainy haze; 2) the depth from the camera determines the degrees of object visibility, where objects nearby and faraway are visually blocked by rain streaks and rainy haze, respectively; and 3) raindrops on the glass randomly affect the object visibility of the whole image space.

Rain Removal

Constrained Multi-shape Evolution for Overlapping Cytoplasm Segmentation

no code implementations8 Apr 2020 Youyi Song, Lei Zhu, Baiying Lei, Bin Sheng, Qi Dou, Jing Qin, Kup-Sze Choi

In the shape evolution, we compensate intensity deficiency for the segmentation by introducing not only the modeled local shape priors but also global shape priors (clump--level) modeled by considering mutual shape constraints of cytoplasms in the clump.

CNN in CT Image Segmentation: Beyound Loss Function for Expoliting Ground Truth Images

no code implementations8 Apr 2020 Youyi Song, Zhen Yu, Teng Zhou, Jeremy Yuen-Chun Teoh, Baiying Lei, Kup-Sze Choi, Jing Qin

Our insight is that feature maps of two CNNs trained respectively on GT and CT images should be similar on some metric space, because they both are used to describe the same objects for the same purpose.

Image Segmentation Semantic Segmentation

Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion

1 code implementation22 Feb 2020 Cheng Chen, Qi Dou, Yueming Jin, Hao Chen, Jing Qin, Pheng-Ann Heng

We tackle this challenge and propose a novel multimodal segmentation framework which is robust to the absence of imaging modalities.

Brain Tumor Segmentation Disentanglement +2

Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

1 code implementation6 Feb 2020 Cheng Chen, Qi Dou, Hao Chen, Jing Qin, Pheng Ann Heng

In this work, we present a novel unsupervised domain adaptation framework, named as Synergistic Image and Feature Alignment (SIFA), to effectively adapt a segmentation network to an unlabeled target domain.

Image Segmentation Medical Image Segmentation +3

Iterative Hard Thresholding for Low CP-rank Tensor Models

no code implementations22 Aug 2019 Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin

In this paper, we utilize the same tensor version of the Restricted Isometry Property (RIP) to extend these results for tensors with low CANDECOMP/PARAFAC (CP) rank.

Convolutional Neural Network with Median Layers for Denoising Salt-and-Pepper Contaminations

1 code implementation18 Aug 2019 Luming Liang, Sen Deng, Lionel Gueguen, Mingqiang Wei, Xinming Wu, Jing Qin

We propose a deep fully convolutional neural network with a new type of layer, named median layer, to restore images contaminated by the salt-and-pepper (s&p) noise.

Salt-And-Pepper Noise Removal

Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis

1 code implementation13 Jul 2019 Yueming Jin, Huaxia Li, Qi Dou, Hao Chen, Jing Qin, Chi-Wing Fu, Pheng-Ann Heng

Mutually leveraging both low-level feature sharing and high-level prediction correlating, our MTRCNet-CL method can encourage the interactions between the two tasks to a large extent, and hence can bring about benefits to each other.

Surgical phase recognition Surgical tool detection

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.

Image Segmentation Medical Image Segmentation +1

Multi-Kernel Correntropy for Robust Learning

no code implementations24 May 2019 Badong Chen, Yuqing Xie, Xin Wang, Zejian yuan, Pengju Ren, Jing Qin

In a recent work, the concept of mixture correntropy (MC) was proposed to improve the learning performance, where the kernel function is a mixture Gaussian kernel, namely a linear combination of several zero-mean Gaussian kernels with different widths.

Structure-Aware 3D Hourglass Network for Hand Pose Estimation from Single Depth Image

no code implementations26 Dec 2018 Fuyang Huang, Ailing Zeng, Minhao Liu, Jing Qin, Qiang Xu

Experimental results show that the proposed structure-aware 3D hourglass network is able to achieve a mean joint error of 7. 4 mm in MSRA and 8. 9 mm in NYU datasets, respectively.

Hand Pose Estimation

Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection

1 code implementation ECCV 2018 Lei Zhu, Zijun Deng, Xiao-Wei Hu, Chi-Wing Fu, Xuemiao Xu, Jing Qin, Pheng-Ann Heng

Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.

Shadow Detection

Direction-aware Spatial Context Features for Shadow Detection and Removal

1 code implementation12 May 2018 Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Jing Qin, Pheng-Ann Heng

This paper presents a novel deep neural network design for shadow detection and removal by analyzing the spatial image context in a direction-aware manner.

Shadow Detection And Removal Shadow Removal

SINet: A Scale-insensitive Convolutional Neural Network for Fast Vehicle Detection

no code implementations2 Apr 2018 Xiaowei Hu, Xuemiao Xu, Yongjie Xiao, Hao Chen, Shengfeng He, Jing Qin, Pheng-Ann Heng

Based on these findings, we present a scale-insensitive convolutional neural network (SINet) for fast detecting vehicles with a large variance of scales.

Fast Vehicle Detection object-detection +1

SFCN-OPI: Detection and Fine-grained Classification of Nuclei Using Sibling FCN with Objectness Prior Interaction

no code implementations22 Dec 2017 Yanning Zhou, Qi Dou, Hao Chen, Jing Qin, Pheng-Ann Heng

Cell nuclei detection and fine-grained classification have been fundamental yet challenging problems in histopathology image analysis.

General Classification

Direction-aware Spatial Context Features for Shadow Detection

1 code implementation CVPR 2018 Xiaowei Hu, Lei Zhu, Chi-Wing Fu, Jing Qin, Pheng-Ann Heng

To achieve this, we first formulate the direction-aware attention mechanism in a spatial recurrent neural network (RNN) by introducing attention weights when aggregating spatial context features in the RNN.

Detecting Shadows Shadow Detection

Automated Pulmonary Nodule Detection via 3D ConvNets with Online Sample Filtering and Hybrid-Loss Residual Learning

no code implementations13 Aug 2017 Qi Dou, Hao Chen, Yueming Jin, Huangjing Lin, Jing Qin, Pheng-Ann Heng

In this paper, we propose a novel framework with 3D convolutional networks (ConvNets) for automated detection of pulmonary nodules from low-dose CT scans, which is a challenging yet crucial task for lung cancer early diagnosis and treatment.

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.

ScanNet: A Fast and Dense Scanning Framework for Metastatic Breast Cancer Detection from Whole-Slide Images

no code implementations30 Jul 2017 Huangjing Lin, Hao Chen, Qi Dou, Liansheng Wang, Jing Qin, Pheng-Ann Heng

Lymph node metastasis is one of the most significant diagnostic indicators in breast cancer, which is traditionally observed under the microscope by pathologists.

Breast Cancer Detection whole slide images

Robust Learning with Kernel Mean p-Power Error Loss

no code implementations21 Dec 2016 Badong Chen, Lei Xing, Xin Wang, Jing Qin, Nanning Zheng

Correntropy is a second order statistical measure in kernel space, which has been successfully applied in robust learning and signal processing.

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.

Image Segmentation Medical Image Segmentation +1

3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes

no code implementations3 Jul 2016 Qi Dou, Hao Chen, Yueming Jin, Lequan Yu, Jing Qin, Pheng-Ann Heng

Automatic liver segmentation from CT volumes is a crucial prerequisite yet challenging task for computer-aided hepatic disease diagnosis and treatment.

Liver Segmentation

A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-norm Fidelity

no code implementations9 Apr 2015 Fang Li, Stanley Osher, Jing Qin, Ming Yan

In this paper, we propose a variational multiphase image segmentation model based on fuzzy membership functions and L1-norm fidelity.

Image Segmentation Semantic Segmentation

Two-stage Geometric Information Guided Image Reconstruction

no code implementations26 Sep 2014 Jing Qin, Weihong Guo

Existing methods mostly work well on piecewise constant images but not so well on piecewise smooth images such as natural images, medical images that contain a lot of details.

Compressive Sensing Image Reconstruction +1

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