490 citations · 1.5k across the 56 of their papers we have counts for
42 papers · 1 filter
RMAFF-PSN: A Residual Multi-Scale Attention Feature Fusion Photometric Stereo Network
Kai Luo, Yakun Ju, Lin Qi +2
Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo metho…
ForensicsForest Family: A Series of Multi-scale Hierarchical Cascade Forests for Detecting GAN-generated Faces
Jiucui Lu, Jiaran Zhou, Junyu Dong +3
The prominent progress in generative models has significantly improved the reality of generated faces, bringing serious concerns to society. Since recent GAN-generated faces are in…
Curricular Contrastive Regularization for Physics-aware Single Image Dehazing
Yu Zheng, Jiahui Zhan, Shengfeng He +2
Considering the ill-posed nature, contrastive regularization has been developed for single image dehazing, introducing the information from negative images as a lower bound. Howeve…
Deep Learning Methods for Calibrated Photometric Stereo and Beyond
Yakun Ju, Kin-Man Lam, Wuyuan Xie +3
Photometric stereo recovers the surface normals of an object from multiple images with varying shading cues, i.e., modeling the relationship between surface orientation and intensi…
Lightweight Monocular Depth Estimation with an Edge Guided Network
Xingshuai Dong, Matthew A. Garratt, Sreenatha G. Anavatti +2
Monocular depth estimation is an important task that can be applied to many robotic applications. Existing methods focus on improving depth estimation accuracy via training increas…
Change Detection from Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network
Junjie Wang, Feng Gao, Junyu Dong +2
Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the field of remote sensing image analysis. Most previous works adopt a self-supervised met…
Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image Classification
Junjie Wang, Feng Gao, Junyu Dong +1
In recent years, hyperspectral image (HSI) classification based on generative adversarial networks (GAN) has achieved great progress. GAN-based classification methods can mitigate…
SurroundNet: Towards Effective Low-Light Image Enhancement
Fei Zhou, Xin Sun, Junyu Dong +2
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 a…
LSENet: Location and Seasonality Enhanced Network for Multi-Class Ocean Front Detection
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…
Incorporating Lambertian Priors into Surface Normals Measurement
Yakun Ju, Muwei Jian, Shaoxiang Guo +3
The goal of photometric stereo is to measure the precise surface normal of a 3D object from observations with various shading cues. However, non-Lambertian surfaces influence the m…
Wallpaper Texture Generation and Style Transfer Based on Multi-label Semantics
Ying Gao, Xiaohan Feng, Tiange Zhang +4
Textures contain a wealth of image information and are widely used in various fields such as computer graphics and computer vision. With the development of machine learning, the te…
Knowledge Distillation via Instance-level Sequence Learning
Haoran Zhao, Xin Sun, Junyu Dong +2
Recently, distillation approaches are suggested to extract general knowledge from a teacher network to guide a student network. Most of the existing methods transfer knowledge from…
Learning the Precise Feature for Cluster Assignment
Yanhai Gan, Xinghui Dong, Huiyu Zhou +2
Clustering is one of the fundamental tasks in computer vision and pattern recognition. Recently, deep clustering methods (algorithms based on deep learning) have attracted wide att…
SAR Image Change Detection Based on Multiscale Capsule Network
Yunhao Gao, Feng Gao, Junyu Dong +1
Traditional change detection methods based on convolutional neural networks (CNNs) face the challenges of speckle noise and deformation sensitivity for synthetic aperture radar ima…
Gaussian Dynamic Convolution for Efficient Single-Image Segmentation
Xin Sun, Changrui Chen, Xiaorui Wang +3
Interactive single-image segmentation is ubiquitous in the scientific and commercial imaging software. In this work, we focus on the single-image segmentation problem only with som…
Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network
Xiaofan Qu, Feng Gao, Junyu Dong +2
Change detection from synthetic aperture radar (SAR) imagery is a critical yet challenging task. Existing methods mainly focus on feature extraction in spatial domain, and little a…
Hyperspectral and LiDAR data classification based on linear self-attention
Min Feng, Feng Gao, Jian Fang +1
An efficient linear self-attention fusion model is proposed in this paper for the task of hyperspectral image (HSI) and LiDAR data joint classification. The proposed method is comp…
Change Detection from SAR Images Based on Deformable Residual Convolutional Neural Networks
Junjie Wang, Feng Gao, Junyu Dong
Convolutional neural networks (CNN) have made great progress for synthetic aperture radar (SAR) images change detection. However, sampling locations of traditional convolutional ke…
Dual Discriminator Adversarial Distillation for Data-free Model Compression
Haoran Zhao, Xin Sun, Junyu Dong +2
Knowledge distillation has been widely used to produce portable and efficient neural networks which can be well applied on edge devices for computer vision tasks. However, almost a…
Remote Sensing Image Translation via Style-Based Recalibration Module and Improved Style Discriminator
Tiange Zhang, Feng Gao, Junyu Dong +1
Existing remote sensing change detection methods are heavily affected by seasonal variation. Since vegetation colors are different between winter and summer, such variations are in…
Similarity Transfer for Knowledge Distillation
Haoran Zhao, Kun Gong, Xin Sun +2
Knowledge distillation is a popular paradigm for learning portable neural networks by transferring the knowledge from a large model into a smaller one. Most existing approaches enh…
Class balanced underwater object detection dataset generated by class-wise style augmentation
Long Chen, Junyu Dong, Huiyu Zhou
Underwater object detection technique is of great significance for various applications in underwater the scenes. However, class imbalance issue is still an unsolved bottleneck for…
Multimodal Gait Recognition for Neurodegenerative Diseases
Aite Zhao, Jianbo Li, Junyu Dong +5
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…
Associated Spatio-Temporal Capsule Network for Gait Recognition
Aite Zhao, Junyu Dong, Jianbo Li +2
It is a challenging task to identify a person based on her/his gait patterns. State-of-the-art approaches rely on the analysis of temporal or spatial characteristics of gait, and g…