1.1k citations · 5.1k across the 81 of their papers we have counts for
21 papers · 1 filter
Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity
Jinglin Xu, Junwei Han, Mingliang Xu +2
Clustering is an effective technique in data mining to group a set of objects in terms of some attributes. Among various clustering approaches, the family of K-Means algorithms gai…
Meta Learning for Task-Driven Video Summarization
Xuelong Li, Hongli Li, Yongsheng Dong
Existing video summarization approaches mainly concentrate on sequential or structural characteristic of video data. However, they do not pay enough attention to the video summariz…
An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms
Feiping Nie, Zhanxuan Hu, Xiaoqian Wang +3
This work aims at solving the problems with intractable sparsity-inducing norms that are often encountered in various machine learning tasks, such as multi-task learning, subspace…
Intrinsic Weight Learning Approach for Multi-view Clustering
Feiping Nie, Jing Li, Xuelong Li
Exploiting different representations, or views, of the same object for better clustering has become very popular these days, which is conventionally called multi-view clustering. G…
Vision-to-Language Tasks Based on Attributes and Attention Mechanism
Xuelong Li, Aihong Yuan, Xiaoqiang Lu
Vision-to-language tasks aim to integrate computer vision and natural language processing together, which has attracted the attention of many researchers. For typical approaches, t…
Learning Feature Sparse Principal Components
Lai Tian, Feiping Nie, Xuelong Li
This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously. Existing optimization met…
PCC Net: Perspective Crowd Counting via Spatial Convolutional Network
Junyu Gao, Qi Wang, Xuelong Li
Crowd counting from a single image is a challenging task due to high appearance similarity, perspective changes and severe congestion. Many methods only focus on the local appearan…
Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification
Qi Wang, Xiange He, Xuelong Li
Hyperspectral image (HSI) classification, which aims to assign an accurate label for hyperspectral pixels, has drawn great interest in recent years. Although low rank representatio…
GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection
Qi Wang, Zhenghang Yuan, Qian Du +1
Change detection (CD) is an important application of remote sensing, which provides timely change information about large-scale Earth surface. With the emergence of hyperspectral i…
Optimal Clustering Framework for Hyperspectral Band Selection
Qi Wang, Fahong Zhang, Xuelong Li
Band selection, by choosing a set of representative bands in hyperspectral image (HSI), is an effective method to reduce the redundant information without compromising the original…
Robust subspace clustering by Cauchy loss function
Xuelong Li, Quanmao Lu, Yongsheng Dong +1
Subspace clustering is a problem of exploring the low-dimensional subspaces of high-dimensional data. State-of-the-arts approaches are designed by following the model of spectral c…
Hierarchical Recurrent Neural Network for Video Summarization
Bin Zhao, Xuelong Li, Xiaoqiang Lu
Exploiting the temporal dependency among video frames or subshots is very important for the task of video summarization. Practically, RNN is good at temporal dependency modeling, a…
A CNN-RNN Architecture for Multi-Label Weather Recognition
Bin Zhao, Xuelong Li, Xiaoqiang Lu +1
Weather Recognition plays an important role in our daily lives and many computer vision applications. However, recognizing the weather conditions from a single image remains challe…
A General Framework for Edited Video and Raw Video Summarization
Xuelong Li, Bin Zhao, Xiaoqiang Lu
In this paper, we build a general summarization framework for both of edited video and raw video summarization. Overall, our work can be divided into three folds: 1) Four models ar…
3G structure for image caption generation
Aihong Yuan, Xuelong Li, Xiaoqiang Lu
It is a big challenge of computer vision to make machine automatically describe the content of an image with a natural language sentence. Previous works have made great progress on…
Multi-modal gated recurrent units for image description
Xuelong Li, Aihong Yuan, Xiaoqiang Lu
Using a natural language sentence to describe the content of an image is a challenging but very important task. It is challenging because a description must not only capture object…
Listen to the Image
Di Hu, Dong Wang, Xuelong Li +2
Visual-to-auditory sensory substitution devices can assist the blind in sensing the visual environment by translating the visual information into a sound pattern. To improve the tr…
Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes
Qi Wang, Junyu Gao, Xuelong Li
Semantic segmentation, a pixel-level vision task, is developed rapidly by using convolutional neural networks (CNNs). Training CNNs requires a large amount of labeled data, but man…
SCE: A manifold regularized set-covering method for data partitioning
Xuelong Li, Quanmao Lu, Yongsheng Dong +1
Cluster analysis plays a very important role in data analysis. In these years, cluster ensemble, as a cluster analysis tool, has drawn much attention for its robustness, stability,…
Patch alignment manifold matting
Xuelong Li, Kang Liu, Yongsheng Dong +1
Image matting is generally modeled as a space transform from the color space to the alpha space. By estimating the alpha factor of the model, the foreground of an image can be extr…
Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning
Shaohui Lin, Rongrong Ji, Yuchao Li +2
The success of convolutional neural networks (CNNs) in computer vision applications has been accompanied by a significant increase of computation and memory costs, which prohibits…