Search Results for author: Junyu Dong

Found 63 papers, 23 papers with code

Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks

no code implementations11 Feb 2023 Wei Chen, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong

Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking different trajectories to users with the exploration of complex mobility patterns.

Nearest Neighbor-Based Contrastive Learning for Hyperspectral and LiDAR Data Classification

no code implementations9 Jan 2023 Meng Wang, Feng Gao, Junyu Dong, Heng-Chao Li, Qian Du

It is commonly nontrivial to build a robust self-supervised learning model for multisource data classification, due to the fact that the semantic similarities of neighborhood regions are not exploited in existing contrastive learning framework.

Classification Contrastive Learning +2

A Deep Learning Method for Real-time Bias Correction of Wind Field Forecasts in the Western North Pacific

no code implementations29 Dec 2022 Wei zhang, Yueyue Jiang, Junyu Dong, Xiaojiang Song, Renbo Pang, Boyu Guoan, Hui Yu

In this study, we developed the Multi-Task-Double Encoder Trajectory Gated Recurrent Unit (MT-DETrajGRU) model, which uses an improved double-encoder forecaster architecture to model the spatiotemporal sequence of the U and V components of the wind field; we designed a multi-task learning loss function to correct wind speed and wind direction simultaneously using only one model.

Multi-Task Learning

Deep Learning Methods for Calibrated Photometric Stereo and Beyond: A Survey

no code implementations16 Dec 2022 Yakun Ju, Kin-Man Lam, Wuyuan Xie, Huiyu Zhou, Junyu Dong, Boxin Shi

We summarize the performance of deep learning photometric stereo models on the most widely-used benchmark data set.

Lightweight Monocular Depth Estimation with an Edge Guided Network

no code implementations29 Sep 2022 Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Hussein A. Abbass, Junyu Dong

In order to aggregate the context information and edge attention features, we design a transformer-based feature aggregation module (TRFA).

Monocular Depth Estimation

Multiplex Heterogeneous Graph Convolutional Network

1 code implementation12 Aug 2022 Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous network data, ranging from link prediction to node classification.

Link Prediction Network Embedding +1

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.

Mutual Distillation Learning Network for Trajectory-User Linking

1 code implementation8 May 2022 Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong

In this paper, we propose a novel Mutual distillation learning network to solve the TUL problem for sparse check-in mobility data, named MainTUL.

Enhancing the Transferability via Feature-Momentum Adversarial Attack

no code implementations22 Apr 2022 Xianglong, Yuezun Li, Haipeng Qu, Junyu Dong

However, the guidance map is fixed in existing methods, which can not consistently reflect the behavior of networks as the image is changed during iteration.

Adversarial Attack

Scalable Motif Counting for Large-scale Temporal Graphs

1 code implementation20 Apr 2022 Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu, Lei Cao, Chao Huang, Junyu Dong

We first categorize the temporal motifs based on their distinct properties, and then design customized algorithms that offer efficient strategies to exactly count the motif instances of each category.

Anomaly Detection Representation Learning

Change Detection from Synthetic Aperture Radar Images via Dual Path Denoising Network

no code implementations13 Mar 2022 Junjie Wang, Feng Gao, Junyu Dong, Qian Du, Heng-Chao Li

We also propose the distinctive patch convolution for feature representation learning to reduce the time consumption.

Change Detection Denoising +1

SSCU-Net: Spatial-Spectral Collaborative Unmixing Network for Hyperspectral Images

no code implementations12 Mar 2022 Lin Qi, Feng Gao, Junyu Dong, Xinbo Gao, Qian Du

Important findings on the use of spatial and spectral information in the autoencoder framework are discussed.

Hyperspectral Unmixing

Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image Classification

1 code implementation22 Jan 2022 Junjie Wang, Feng Gao, Junyu Dong, Qian Du

Second, an adaptive DropBlock (AdapDrop) is proposed as a regularization method employed in the generator and discriminator to alleviate the mode collapse issue.

Classification Hyperspectral Image Classification

SAR Image Change Detection Based on Multiscale Capsule Network

1 code implementation22 Jan 2022 Yunhao Gao, Feng Gao, Junyu Dong, Heng-Chao Li

On the one hand, the multiscale capsule module is employed to exploit the spatial relationship of features.

Change Detection

Change Detection from Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network

1 code implementation22 Jan 2022 Junjie Wang, Feng Gao, Junyu Dong, Shan Zhang, Qian Du

Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the field of remote sensing image analysis.

Change Detection

Physics-Guided Generative Adversarial Networks for Sea Subsurface Temperature Prediction

1 code implementation4 Nov 2021 Yuxin Meng, Eric Rigall, Xueen Chen, Feng Gao, Junyu Dong, Sheng Chen

Physical modeling methods can offer the potential for extrapolation beyond observational conditions, while data-driven methods are flexible in adapting to data and are capable of detecting unexpected patterns.

Synthetic Aperture Radar Image Change Detection via Siamese Adaptive Fusion Network

1 code implementation18 Oct 2021 Yunhao Gao, Feng Gao, Junyu Dong, Qian Du, Heng-Chao Li

Moreover, a correlation layer is designed to further explore the correlation between multitemporal images.

Change Detection

SurroundNet: Towards Effective Low-Light Image Enhancement

1 code implementation11 Oct 2021 Fei Zhou, Xin Sun, Junyu Dong, Haoran Zhao, Xiao Xiang Zhu

Although Convolution Neural Networks (CNNs) has made substantial progress in the low-light image enhancement task, one critical problem of CNNs is the paradox of model complexity and performance.

Low-Light Image Enhancement

LSENet: Location and Seasonality Enhanced Network for Multi-Class Ocean Front Detection

no code implementations5 Aug 2021 Cui Xie, Hao Guo, Junyu Dong

Ocean fronts can cause the accumulation of nutrients and affect the propagation of underwater sound, so high-precision ocean front detection is of great significance to the marine fishery and national defense fields.

Semantic Segmentation

Incorporating Lambertian Priors into Surface Normals Measurement

no code implementations15 Jul 2021 Yakun Ju, Muwei Jian, Shaoxiang Guo, YingYu Wang, Huiyu Zhou, Junyu Dong

In order to address this challenge, we here propose a photometric stereo network that incorporates Lambertian priors to better measure the surface normal.

Wallpaper Texture Generation and Style Transfer Based on Multi-label Semantics

no code implementations22 Jun 2021 Ying Gao, Xiaohan Feng, Tiange Zhang, Eric Rigall, Huiyu Zhou, Lin Qi, Junyu Dong

Textures contain a wealth of image information and are widely used in various fields such as computer graphics and computer vision.

Style Transfer Texture Synthesis

Knowledge Distillation via Instance-level Sequence Learning

no code implementations21 Jun 2021 Haoran Zhao, Xin Sun, Junyu Dong, Zihe Dong, Qiong Li

Recently, distillation approaches are suggested to extract general knowledge from a teacher network to guide a student network.

General Knowledge Knowledge Distillation

SAR Image Change Detection Based on Multiscale Capsule Network

1 code implementation13 Jun 2021 Yunhao Gao, Feng Gao, Junyu Dong, Heng-Chao Li

On the one hand, the capsule module is employed to exploit the spatial relationship of features.

Change Detection

Learning the Precise Feature for Cluster Assignment

1 code implementation11 Jun 2021 Yanhai Gan, Xinghui Dong, Huiyu Zhou, Feng Gao, Junyu Dong

Based on this, we propose a general-purpose deep clustering framework which radically integrates representation learning and clustering into a single pipeline for the first time.

Deep Clustering Face Recognition +3

Network Embedding via Deep Prediction Model

no code implementations27 Apr 2021 Xin Sun, Zenghui Song, Yongbo Yu, Junyu Dong, Claudia Plant, Christian Boehm

This paper proposes a network embedding framework to capture the transfer behaviors on structured networks via deep prediction models.

Feature Engineering Link Prediction +1

Gaussian Dynamic Convolution for Efficient Single-Image Segmentation

no code implementations18 Apr 2021 Xin Sun, Changrui Chen, Xiaorui Wang, Junyu Dong, Huiyu Zhou, Sheng Chen

Furthermore, we also build a Gaussian dynamic pyramid Pooling to show its potential and generality in common semantic segmentation.

Image Segmentation Semantic Segmentation

Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network

1 code implementation14 Apr 2021 Xiaofan Qu, Feng Gao, Junyu Dong, Qian Du, Heng-Chao Li

In addition, we further propose a multi-region convolution module, which emphasizes the central region of each patch.

Change Detection

Dual Discriminator Adversarial Distillation for Data-free Model Compression

no code implementations12 Apr 2021 Haoran Zhao, Xin Sun, Junyu Dong, Hui Yu, Huiyu Zhou

Then the generated samples are used to train the compact student network under the supervision of the teacher.

Knowledge Distillation Model Compression +1

Change Detection from SAR Images Based on Deformable Residual Convolutional Neural Networks

no code implementations6 Apr 2021 Junjie Wang, Feng Gao, Junyu Dong

Convolutional neural networks (CNN) have made great progress for synthetic aperture radar (SAR) images change detection.

Change Detection

Hyperspectral and LiDAR data classification based on linear self-attention

no code implementations6 Apr 2021 Min Feng, Feng Gao, Jian Fang, Junyu Dong

An efficient linear self-attention fusion model is proposed in this paper for the task of hyperspectral image (HSI) and LiDAR data joint classification.

Classification General Classification

Disentangled Non-Local Network for Hyperspectral and LiDAR Data Classification

no code implementations6 Apr 2021 Wenxia Liu, Feng Gao, Junyu Dong

As the ground objects become increasingly complex, the classification results obtained by single source remote sensing data can hardly meet the application requirements.

Classification General Classification

Similarity Transfer for Knowledge Distillation

no code implementations18 Mar 2021 Haoran Zhao, Kun Gong, Xin Sun, Junyu Dong, Hui Yu

The proposed approach promotes the performance of student model as the virtual sample created by multiple images produces a similar probability distribution in the teacher and student networks.

Knowledge Distillation

Class balanced underwater object detection dataset generated by class-wise style augmentation

no code implementations20 Jan 2021 Long Chen, Junyu Dong, Huiyu Zhou

CWSA is a new kind of data augmentation technique which augments the training data for the minority classes by generating various colors, textures and contrasts for the minority classes.

Data Augmentation object-detection +1

Multimodal Gait Recognition for Neurodegenerative Diseases

1 code implementation7 Jan 2021 Aite Zhao, Jianbo Li, Junyu Dong, Lin Qi, Qianni Zhang, Ning li, Xin Wang, Huiyu Zhou

In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the established approaches has different strengths and weaknesses.

Gait Recognition

Image Harmonization With Transformer

1 code implementation ICCV 2021 Zonghui Guo, Dongsheng Guo, Haiyong Zheng, Zhaorui Gu, Bing Zheng, Junyu Dong

Current solutions mainly adopt an encoder-decoder architecture with convolutional neural network (CNN) to capture the context of composite images, trying to understand what it looks like in the surrounding background near the foreground.

Disentanglement Image Harmonization +1

Multi-Modal Multi-Action Video Recognition

1 code implementation ICCV 2021 Zhensheng Shi, Ju Liang, Qianqian Li, Haiyong Zheng, Zhaorui Gu, Junyu Dong, Bing Zheng

In this paper, we propose a novel multi-action relation model for videos, by leveraging both relational graph convolutional networks (GCNs) and video multi-modality.

Video Recognition

Low-Rank Tensor Completion by Approximating the Tensor Average Rank

no code implementations ICCV 2021 Zhanliang Wang, Junyu Dong, Xinguo Liu, Xueying Zeng

Our method is motivated by the recently proposed t-product based on any invertible linear transforms.

SWIPENET: Object detection in noisy underwater images

1 code implementation19 Oct 2020 Long Chen, Feixiang Zhou, Shengke Wang, Junyu Dong, Ning li, Haiping Ma, Xin Wang, Huiyu Zhou

Moreover, inspired by the human education process that drives the learning from easy to hard concepts, we here propose the CMA training paradigm that first trains a clean detector which is free from the influence of noisy data.

object-detection Small Object Detection

Real-time 3D Facial Tracking via Cascaded Compositional Learning

1 code implementation2 Sep 2020 Jianwen Lou, Xiaoxu Cai, Junyu Dong, Hui Yu

We propose to learn a cascade of globally-optimized modular boosted ferns (GoMBF) to solve multi-modal facial motion regression for real-time 3D facial tracking from a monocular RGB camera.


3D Facial Geometry Recovery from a Depth View with Attention Guided Generative Adversarial Network

no code implementations2 Sep 2020 Xiaoxu Cai, Hui Yu, Jianwen Lou, Xuguang Zhang, Gongfa Li, Junyu Dong

We present to recover the complete 3D facial geometry from a single depth view by proposing an Attention Guided Generative Adversarial Networks (AGGAN).

Perceptual underwater image enhancement with deep learning and physical priors

no code implementations21 Aug 2020 Long Chen, Zheheng Jiang, Lei Tong, Zhihua Liu, Aite Zhao, Qianni Zhang, Junyu Dong, Huiyu Zhou

Underwater image enhancement, as a pre-processing step to improve the accuracy of the following object detection task, has drawn considerable attention in the field of underwater navigation and ocean exploration.

Image Enhancement Image Generation +2

A Benchmark dataset for both underwater image enhancement and underwater object detection

no code implementations29 Jun 2020 Long Chen, Lei Tong, Feixiang Zhou, Zheheng Jiang, Zhenyang Li, Jialin Lv, Junyu Dong, Huiyu Zhou

To investigate how the underwater image enhancement methods influence the following underwater object detection tasks, in this paper, we provide a large-scale underwater object detection dataset with both bounding box annotations and high quality reference images, namely OUC dataset.

Image Enhancement Image Quality Assessment +2

Progressively Unfreezing Perceptual GAN

no code implementations18 Jun 2020 Jinxuan Sun, Yang Chen, Junyu Dong, Guoqiang Zhong

Generative adversarial networks (GANs) are widely used in image generation tasks, yet the generated images are usually lack of texture details.

Image Super-Resolution Image-to-Image Translation +1

Underwater object detection using Invert Multi-Class Adaboost with deep learning

1 code implementation23 May 2020 Long Chen, Zhihua Liu, Lei Tong, Zheheng Jiang, Shengke Wang, Junyu Dong, Huiyu Zhou

In addition, we propose a novel sample-weighted loss function which can model sample weights for SWIPENet, which uses a novel sample re-weighting algorithm, namely Invert Multi-Class Adaboost (IMA), to reduce the influence of noise on the proposed SWIPENet.

object-detection Small Object Detection

High-Order Paired-ASPP Networks for Semantic Segmenation

no code implementations18 Feb 2020 Yu Zhang, Xin Sun, Junyu Dong, Changrui Chen, Yue Shen

The network first introduces a High-Order Representation module to extract the contextual high-order information from all stages of the backbone.

Semantic Segmentation

Multi-level Similarity Learning for Low-Shot Recognition

no code implementations13 Dec 2019 Hongwei Xv, Xin Sun, Junyu Dong, Shu Zhang, Qiong Li

Low-shot learning indicates the ability to recognize unseen objects based on very limited labeled training samples, which simulates human visual intelligence.

Few-shot Learning for Domain-specific Fine-grained Image Classification

no code implementations23 Jul 2019 Xin Sun, Hongwei Xv, Junyu Dong, Qiong Li, Changrui Chen

Learning to recognize novel visual categories from a few examples is a challenging task for machines in real-world industrial applications.

Classification Few-Shot Learning +2

Highlight Every Step: Knowledge Distillation via Collaborative Teaching

1 code implementation23 Jul 2019 Haoran Zhao, Xin Sun, Junyu Dong, Changrui Chen, Zihe Dong

Knowledge distillation aims to train a compact student network by transferring knowledge from a larger pre-trained teacher model.

Knowledge Distillation

Combining SLAM with muti-spectral photometric stereo for real-time dense 3D reconstruction

no code implementations6 Jul 2018 Yuanhong Xu, Pei Dong, Junyu Dong, Lin Qi

Obtaining dense 3D reconstrution with low computational cost is one of the important goals in the field of SLAM.

3D Reconstruction

Dense 3D Facial Reconstruction from a Single Depth Image in Unconstrained Environment

no code implementations24 Apr 2017 Shu Zhang, Hui Yu, Ting Wang, Junyu Dong, Honghai Liu

With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is considered to be more and more important as a fundamental step for those virtual reality tasks.

A Procedural Texture Generation Framework Based on Semantic Descriptions

no code implementations13 Apr 2017 Junyu Dong, Li-Na Wang, Jun Liu, Xin Sun

Finally, given a set of semantic descriptions, the diverse properties of the samples in the semantic space can lead the framework to find an appropriate generation model that uses appropriate parameters to produce a desired texture.

Multi-Label Learning Texture Synthesis

Perception Driven Texture Generation

no code implementations24 Mar 2017 Yanhai Gan, Huifang Chi, Ying Gao, Jun Liu, Guoqiang Zhong, Junyu Dong

In this paper, we propose a joint deep network model that combines adversarial training and perceptual feature regression for texture generation, while only random noise and user-defined perceptual attributes are required as input.

Texture Synthesis

Cascade one-vs-rest detection network for fine-grained recognition without part annotations

no code implementations28 Feb 2017 Long Chen, Junyu Dong, Shengke Wang, Kin-Man Lam, Muwei Jian, Hua Zhang, Xiaochun Cao

To bridge this gap, we introduce a cascaded structure to eliminate background and exploit a one-vs-rest loss to capture more minute variances among different subordinate categories.

An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning

no code implementations25 Nov 2016 Guoqiang Zhong, Li-Na Wang, Junyu Dong

Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, including both linear ones and nonlinear ones, supervised ones and unsupervised ones.

General Classification Image Classification +5

Banzhaf Random Forests

no code implementations22 Jul 2015 Jianyuan Sun, Guoqiang Zhong, Junyu Dong, Yajuan Cai

Random forests are a type of ensemble method which makes predictions by combining the results of several independent trees.

A Deep Hashing Learning Network

no code implementations16 Jul 2015 Guoqiang Zhong, Pan Yang, Sijiang Wang, Junyu Dong

For most existing hashing methods, an image is first encoded as a vector of hand-crafted visual feature, followed by a hash projection and quantization step to get the compact binary vector.


A PCA-Based Convolutional Network

no code implementations14 May 2015 Yanhai Gan, Jun Liu, Junyu Dong, Guoqiang Zhong

Particularly, each feature extraction stage includes two layers: a convolutional layer and a feature pooling layer.

Face Recognition Texture Classification

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