193 citations · 785 across the 23 of their papers we have counts for
23 papers
Dual-Perspective United Transformer for Object Segmentation in Optical Remote Sensing Images
Yanguang Sun, Jiexi Yan, Jianjun Qian +3
Automatically segmenting objects from optical remote sensing images (ORSIs) is an important task. Most existing models are primarily based on either convolutional or Transformer fe…
Multi-level Attention-guided Graph Neural Network for Image Restoration
Jiatao Jiang, Zhen Cui, Chunyan Xu +1
In recent years, deep learning has achieved remarkable success in the field of image restoration. However, most convolutional neural network-based methods typically focus on a sing…
Frequency-Spatial Entanglement Learning for Camouflaged Object Detection
Yanguang Sun, Chunyan Xu, Jian Yang +2
Camouflaged object detection has attracted a lot of attention in computer vision. The main challenge lies in the high degree of similarity between camouflaged objects and their sur…
Learning Normal Dynamics in Videos with Meta Prototype Network
Hui Lv, Chen Chen, Zhen Cui +3
Frame reconstruction (current or future frame) based on Auto-Encoder (AE) is a popular method for video anomaly detection. With models trained on the normal data, the reconstructio…
Global Information Guided Video Anomaly Detection
Hui Lv, Chunyan Xu, Zhen Cui
Video anomaly detection (VAD) is currently a challenging task due to the complexity of anomaly as well as the lack of labor-intensive temporal annotations. In this paper, we propos…
Spatial-Temporal Tensor Graph Convolutional Network for Traffic Prediction
Xuran Xu, Tong Zhang, Chunyan Xu +2
Accurate traffic prediction is crucial to the guidance and management of urban traffics. However, most of the existing traffic prediction models do not consider the computational b…
Attention-Aware Noisy Label Learning for Image Classification
Zhenzhen Wang, Chunyan Xu, Yap-Peng Tan +1
Deep convolutional neural networks (CNNs) learned on large-scale labeled samples have achieved remarkable progress in computer vision, such as image/video classification. The cheap…
Spatial Transformer Point Convolution
Yuan Fang, Chunyan Xu, Zhen Cui +2
Point clouds are unstructured and unordered in the embedded 3D space. In order to produce consistent responses under different permutation layouts, most existing methods aggregate…
Instance-Aware Graph Convolutional Network for Multi-Label Classification
Yun Wang, Tong Zhang, Zhen Cui +2
Graph convolutional neural network (GCN) has effectively boosted the multi-label image recognition task by introducing label dependencies based on statistical label co-occurrence o…
Localizing Anomalies from Weakly-Labeled Videos
Hui Lv, Chuanwei Zhou, Chunyan Xu +2
Video anomaly detection under video-level labels is currently a challenging task. Previous works have made progresses on discriminating whether a video sequencecontains anomalies.…
Graph Inference Learning for Semi-supervised Classification
Chunyan Xu, Zhen Cui, Xiaobin Hong +3
In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures. Re…
Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation
Zhenyu Zhang, Zhen Cui, Chunyan Xu +3
In this paper, we propose a novel Pattern-Affinitive Propagation (PAP) framework to jointly predict depth, surface normal and semantic segmentation. The motivation behind it comes…
Gaussian-Induced Convolution for Graphs
Jiatao Jiang, Zhen Cui, Chunyan Xu +1
Learning representation on graph plays a crucial role in numerous tasks of pattern recognition. Different from grid-shaped images/videos, on which local convolution kernels can be…
Context-Dependent Diffusion Network for Visual Relationship Detection
Zhen Cui, Chunyan Xu, Wenming Zheng +1
Visual relationship detection can bridge the gap between computer vision and natural language for scene understanding of images. Different from pure object recognition tasks, the r…
When Work Matters: Transforming Classical Network Structures to Graph CNN
Wenting Zhao, Chunyan Xu, Zhen Cui +4
Numerous pattern recognition applications can be formed as learning from graph-structured data, including social network, protein-interaction network, the world wide web data, know…
Walk-Steered Convolution for Graph Classification
Jiatao Jiang, Chunyan Xu, Zhen Cui +3
Graph classification is a fundamental but challenging issue for numerous real-world applications. Despite recent great progress in image/video classification, convolutional neural…
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition
Chaolong Li, Zhen Cui, Wenming Zheng +2
Variations of human body skeletons may be considered as dynamic graphs, which are generic data representation for numerous real-world applications. In this paper, we propose a spat…
Action-Attending Graphic Neural Network
Chaolong Li, Zhen Cui, Wenming Zheng +3
The motion analysis of human skeletons is crucial for human action recognition, which is one of the most active topics in computer vision. In this paper, we propose a fully end-to-…
MemNet: A Persistent Memory Network for Image Restoration
Ying Tai, Jian Yang, Xiaoming Liu +1
Recently, very deep convolutional neural networks (CNNs) have been attracting considerable attention in image restoration. However, as the depth grows, the long-term dependency pro…
Spectral Filter Tracking
Zhen Cui, You yi Cai, Wen ming Zheng +1
Visual object tracking is a challenging computer vision task with numerous real-world applications. Here we propose a simple but efficient Spectral Filter Tracking (SFT)method. To…
Deep Learning with S-shaped Rectified Linear Activation Units
Xiaojie Jin, Chunyan Xu, Jiashi Feng +3
Rectified linear activation units are important components for state-of-the-art deep convolutional networks. In this paper, we propose a novel S-shaped rectified linear activation…
Deep Recurrent Regression for Facial Landmark Detection
Hanjiang Lai, Shengtao Xiao, Yan Pan +5
We propose a novel end-to-end deep architecture for face landmark detection, based on a deep convolutional and deconvolutional network followed by carefully designed recurrent netw…
Generalized Singular Value Thresholding
Canyi Lu, Changbo Zhu, Chunyan Xu +2
This work studies the Generalized Singular Value Thresholding (GSVT) operator , \begin{equation*} {\text{Prox}}_{g}^{σ}(B)=\arg\min\limits_{X}\sum_{i=…