Search Results for author: Xuelong. Li

Found 61 papers, 10 papers with code

A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View

no code implementations29 Sep 2020 Zhiyuan Zhao, Tao Han, Junyu. Gao, Qi. Wang, Xuelong. Li

Drones shooting can be applied in dynamic traffic monitoring, object detecting and tracking, and other vision tasks.

Crowd Counting Density Estimation +1

Unsupervised Graph Embedding via Adaptive Graph Learning

no code implementations10 Mar 2020 Rui Zhang, Yunxing Zhang, Xuelong. Li

Moreover, the adjacency matrix can be self-learned for better embedding performance when the original graph structure is incomplete.

graph construction Graph Embedding +5

Pixel-Level Self-Paced Learning for Super-Resolution

1 code implementation6 Mar 2020 Wei. Lin, Junyu. Gao, Qi. Wang, Xuelong. Li

Recently, lots of deep networks are proposed to improve the quality of predicted super-resolution (SR) images, due to its widespread use in several image-based fields.


Adaptive Graph Auto-Encoder for General Data Clustering

1 code implementation20 Feb 2020 Xuelong. Li, Hongyuan Zhang, Rui Zhang

Therefore, how to extend graph convolution networks into general clustering tasks is an attractive problem.

Graph Embedding Network Embedding

NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization

4 code implementations10 Jan 2020 Qi. Wang, Junyu. Gao, Wei. Lin, Xuelong. Li

In the last decade, crowd counting and localization attract much attention of researchers due to its wide-spread applications, including crowd monitoring, public safety, space design, etc.

Crowd Counting

Robust and Efficient Fuzzy C-Means Clustering Constrained on Flexible Sparsity

no code implementations19 Aug 2019 Jinglin Xu, Junwei Han, Mingliang Xu, Feiping Nie, Xuelong. Li

Clustering is an effective technique in data mining to group a set of objects in terms of some attributes.

Meta Learning for Task-Driven Video Summarization

no code implementations29 Jul 2019 Xuelong. Li, Hongli Li, Yongsheng Dong

Particularly, MetaL-TDVS aims to excavate the latent mechanism for summarizing video by reformulating video summarization as a meta learning problem and promote generalization ability of the trained model.

Meta-Learning Video Summarization

An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms

no code implementations2 Jul 2019 Feiping Nie, Zhanxuan Hu, Xiaoqian Wang, Rong Wang, Xuelong. Li, Heng Huang

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 clustering, feature selection, robust principal component analysis, and so on.

feature selection Multi-Task Learning

Intrinsic Weight Learning Approach for Multi-view Clustering

no code implementations21 Jun 2019 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.

Vision-to-Language Tasks Based on Attributes and Attention Mechanism

no code implementations29 May 2019 Xuelong. Li, Aihong Yuan, Xiaoqiang Lu

To make full use of these information, this paper attempt to exploit the text guided attention and semantic-guided attention (SA) to find the more correlated spatial information and reduce the semantic gap between vision and language.

Computer Vision Image Captioning +3

PCC Net: Perspective Crowd Counting via Spatial Convolutional Network

1 code implementation24 May 2019 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.

Crowd Counting

Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification

no code implementations7 May 2019 Qi. Wang, Xiange He, Xuelong. Li

In this paper, a novel locality and structure regularized low rank representation (LSLRR) model is proposed for HSI classification.

General Classification Hyperspectral Image Classification

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

no code implementations5 May 2019 Qi. Wang, Senior Member, Zhenghang Yuan, Qian Du, Xuelong. Li, Fellow, IEEE

In order to better handle high dimension problem and explore abundance information, this paper presents a General End-to-end Two-dimensional CNN (GETNET) framework for hyperspectral image change detection (HSI-CD).

Change Detection

Optimal Clustering Framework for Hyperspectral Band Selection

no code implementations30 Apr 2019 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 contents.

Hierarchical Recurrent Neural Network for Video Summarization

no code implementations28 Apr 2019 Bin Zhao, Xuelong. Li, Xiaoqiang Lu

Compared to traditional RNNs, H-RNN is more suitable to video summarization, since it can exploit long temporal dependency among frames, meanwhile, the computation operations are significantly lessened.

Video Captioning Video Summarization

Robust subspace clustering by Cauchy loss function

no code implementations28 Apr 2019 Xuelong. Li, Quanmao Lu, Yongsheng Dong, DaCheng Tao

This is due to that the CLF's influence function has a upper bound which can alleviate the influence of a single sample, especially the sample with a large noise, on estimating the residuals.

A CNN-RNN Architecture for Multi-Label Weather Recognition

no code implementations24 Apr 2019 Bin Zhao, Xuelong. Li, Xiaoqiang Lu, Zhigang Wang

To address this problem, we make the first attempt to view weather recognition as a multi-label classification task, i. e., assigning an image more than one labels according to the displayed weather conditions.

Computer Vision General Classification +1

A General Framework for Edited Video and Raw Video Summarization

no code implementations24 Apr 2019 Xuelong. Li, Bin Zhao, Xiaoqiang Lu

Besides, the property-weights are learned for edited videos and raw videos, respectively.

Video Summarization

Learning Feature Sparse Principal Components

no code implementations23 Apr 2019 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.

feature selection

3G structure for image caption generation

no code implementations21 Apr 2019 Aihong Yuan, Xuelong. Li, Xiaoqiang Lu

In this paper, we propose a model with 3-gated model which fuses the global and local image features together for the task of image caption generation.

Computer Vision

Multi-modal gated recurrent units for image description

no code implementations20 Apr 2019 Xuelong. Li, Aihong Yuan, Xiaoqiang Lu

And in the testing step, when an image is imported to our multi-modal GRU model, a sentence which describes the image content is generated.

Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes

no code implementations19 Apr 2019 Qi. Wang, Junyu. Gao, Xuelong. Li

In this paper, we propose a weakly supervised adversarial domain adaptation to improve the segmentation performance from synthetic data to real scenes, which consists of three deep neural networks.

Domain Adaptation Semantic Segmentation

Listen to the Image

no code implementations CVPR 2019 Di Hu, Dong Wang, Xuelong. Li, Feiping Nie, Qi. Wang

different encoding schemes indicate that using machine model to accelerate optimization evaluation and reduce experimental cost is feasible to some extent, which could dramatically promote the upgrading of encoding scheme then help the blind to improve their visual perception ability.


SCE: A manifold regularized set-covering method for data partitioning

no code implementations17 Apr 2019 Xuelong. Li, Quanmao Lu, Yongsheng Dong, DaCheng Tao

Moreover, considering the importance of the discriminative information underlying in the initial clustering results, we add a discriminative constraint into our proposed objective function.

Patch alignment manifold matting

no code implementations16 Apr 2019 Xuelong. Li, Kang Liu, Yongsheng Dong, DaCheng Tao

In this paper, a manifold matting framework named Patch Alignment Manifold Matting is proposed for image matting.

Image Matting

Towards Compact ConvNets via Structure-Sparsity Regularized Filter Pruning

1 code implementation23 Jan 2019 Shaohui Lin, Rongrong Ji, Yuchao Li, Cheng Deng, Xuelong. Li

In this paper, we propose a novel filter pruning scheme, termed structured sparsity regularization (SSR), to simultaneously speedup the computation and reduce the memory overhead of CNNs, which can be well supported by various off-the-shelf deep learning libraries.

Computer Vision Domain Adaptation +3

Dense Multimodal Fusion for Hierarchically Joint Representation

no code implementations8 Oct 2018 Di Hu, Feiping Nie, Xuelong. Li

Hence, it is highly expected to learn effective joint representation by fusing the features of different modalities.

Cross-Modal Retrieval speech-recognition +1

Deep LDA Hashing

no code implementations8 Oct 2018 Di Hu, Feiping Nie, Xuelong. Li

The conventional supervised hashing methods based on classification do not entirely meet the requirements of hashing technique, but Linear Discriminant Analysis (LDA) does.

Triply Supervised Decoder Networks for Joint Detection and Segmentation

no code implementations CVPR 2019 Jiale Cao, Yanwei Pang, Xuelong. Li

Experimental results on the VOC2007 and VOC2012 datasets demonstrate that the proposed TripleNet is able to improve both the detection and segmentation accuracies without adding extra computational costs.

object-detection Object Detection +2

Deep Smoke Segmentation

no code implementations4 Sep 2018 Feiniu Yuan, Lin Zhang, Xue Xia, Boyang Wan, Qinghua Huang, Xuelong. Li

According to results of our deep segmentation method, we can easily and accurately perform smoke detection from videos.

Semantic Segmentation

TLR: Transfer Latent Representation for Unsupervised Domain Adaptation

no code implementations19 Aug 2018 Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong. Li

Many classic methods solve the domain adaptation problem by establishing a common latent space, which may cause the loss of many important properties across both domains.

Unsupervised Domain Adaptation

Deep Multimodal Clustering for Unsupervised Audiovisual Learning

1 code implementation CVPR 2019 Di Hu, Feiping Nie, Xuelong. Li

And such integrated multimodal clustering network can be effectively trained with max-margin loss in the end-to-end fashion.

HSA-RNN: Hierarchical Structure-Adaptive RNN for Video Summarization

no code implementations CVPR 2018 Bin Zhao, Xuelong. Li, Xiaoqiang Lu

Although video summarization has achieved great success in recent years, few approaches have realized the influence of video structure on the summarization results.

Video Summarization

Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection

no code implementations3 Apr 2018 Jiale Cao, Yanwei Pang, Xuelong. Li

In this paper, we propose a multi-branch and high-level semantic network by gradually splitting a base network into multiple different branches.

object-detection Object Detection +1

PixelLink: Detecting Scene Text via Instance Segmentation

6 code implementations4 Jan 2018 Dan Deng, Haifeng Liu, Xuelong. Li, Deng Cai

Most state-of-the-art scene text detection algorithms are deep learning based methods that depend on bounding box regression and perform at least two kinds of predictions: text/non-text classification and location regression.

Instance Segmentation Scene Text Detection +2

Exploring Models and Data for Remote Sensing Image Caption Generation

1 code implementation21 Dec 2017 Xiaoqiang Lu, Binqiang Wang, Xiangtao Zheng, Xuelong. Li

Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption.

Scene Classification

Video Summarization with Attention-Based Encoder-Decoder Networks

no code implementations31 Aug 2017 Zhong Ji, Kailin Xiong, Yanwei Pang, Xuelong. Li

This paper addresses the problem of supervised video summarization by formulating it as a sequence-to-sequence learning problem, where the input is a sequence of original video frames, the output is a keyshot sequence.

Supervised Video Summarization

Image2song: Song Retrieval via Bridging Image Content and Lyric Words

no code implementations ICCV 2017 Xuelong. Li, Di Hu, Xiaoqiang Lu

Image is usually taken for expressing some kinds of emotions or purposes, such as love, celebrating Christmas.


Deep Binary Reconstruction for Cross-modal Hashing

1 code implementation17 Aug 2017 Xuelong. Li, Di Hu, Feiping Nie

Based on the analysis, we provide a so-called Deep Binary Reconstruction (DBRC) network that can directly learn the binary hashing codes in an unsupervised fashion.

Cross-Modal Retrieval

From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning

no code implementations8 Aug 2017 Jingkuan Song, Yuyu Guo, Lianli Gao, Xuelong. Li, Alan Hanjalic, Heng Tao Shen

In this paper, we propose a generative approach, referred to as multi-modal stochastic RNNs networks (MS-RNN), which models the uncertainty observed in the data using latent stochastic variables.

Video Captioning

Query-Aware Sparse Coding for Multi-Video Summarization

no code implementations13 Jul 2017 Zhong Ji, Yaru Ma, Yanwei Pang, Xuelong. Li

Given the explosive growth of online videos, it is becoming increasingly important to relieve the tedious work of browsing and managing the video content of interest.

Video Summarization

Object Discovery via Cohesion Measurement

no code implementations28 Apr 2017 Guanjun Guo, Hanzi Wang, Wan-Lei Zhao, Yan Yan, Xuelong. Li

Based on the new Cohesion Measurement, a novel object discovery method is proposed to discover objects latent in an image by utilizing the eigenvectors of the affinity matrix.

Computer Vision Object Discovery +3

Constrained Low-Rank Learning Using Least Squares-Based Regularization

no code implementations15 Nov 2016 Ping Li, Jun Yu, Meng Wang, Luming Zhang, Deng Cai, Xuelong. Li

To achieve this goal, we cast the problem into a constrained rank minimization framework by adopting the least squares regularization.

General Classification Image Categorization +2

Temporal Multimodal Learning in Audiovisual Speech Recognition

no code implementations CVPR 2016 Di Hu, Xuelong. Li, Xiaoqiang Lu

Recently, audiovisual speech recognition based the MRBM has attracted much attention, and the MRBM shows its effectiveness in learning the joint representation across audiovisual modalities.

Multimodal Deep Learning speech-recognition +1

Convolution in Convolution for Network in Network

no code implementations22 Mar 2016 Yanwei Pang, Manli Sun, Xiaoheng Jiang, Xuelong. Li

In this paper, we propose to replace dense shallow MLP with sparse shallow MLP.

Cascaded Subpatch Networks for Effective CNNs

no code implementations1 Mar 2016 Xiaoheng Jiang, Yanwei Pang, Manli Sun, Xuelong. Li

The first one is a linear filter of spatial size $ h\times w $ and is aimed at extracting features from spatial domain.

Learning Multilayer Channel Features for Pedestrian Detection

no code implementations1 Mar 2016 Jiale Cao, Yanwei Pang, Xuelong. Li

For example, CNN classifies these proposals by the full-connected layer features while proposal scores and the features in the inner-layers of CNN are ignored.

Pedestrian Detection

A survey of sparse representation: algorithms and applications

no code implementations23 Feb 2016 Zheng Zhang, Yong Xu, Jian Yang, Xuelong. Li, David Zhang

The main purpose of this article is to provide a comprehensive study and an updated review on sparse representation and to supply a guidance for researchers.

Computer Vision

DISC: Deep Image Saliency Computing via Progressive Representation Learning

no code implementations13 Nov 2015 Tianshui Chen, Liang Lin, Lingbo Liu, Xiaonan Luo, Xuelong. Li

Our DISC framework is capable of uniformly highlighting the objects-of-interest from complex background while preserving well object details.

object-detection Representation Learning +2

Moving Object Detection in Video Using Saliency Map and Subspace Learning

no code implementations30 Sep 2015 Yanwei Pang, Li Ye, Xuelong. Li, Jing Pan

So there are undesirable false alarms and missed alarms in many algorithms of moving object detection.

Moving Object Detection object-detection

Learning Sampling Distributions for Efficient Object Detection

no code implementations23 Aug 2015 Yanwei Pang, Jiale Cao, Xuelong. Li

Multistage particle windows (MPW), proposed by Gualdi et al., is an algorithm of fast and accurate object detection.

Computer Vision Face Detection +2

Cascade Learning by Optimally Partitioning

no code implementations18 Aug 2015 Yanwei Pang, Jiale Cao, Xuelong. Li

iCascade searches the optimal number ri of weak classifiers of each stage i by directly minimizing the computation cost of the cascade.

Face Detection object-detection +1

A Maximum Entropy Feature Descriptor for Age Invariant Face Recognition

no code implementations CVPR 2015 Dihong Gong, Zhifeng Li, DaCheng Tao, Jianzhuang Liu, Xuelong. Li

In this paper, we propose a new approach to overcome the representation and matching problems in age invariant face recognition.

Age-Invariant Face Recognition

Facial Feature Point Detection: A Comprehensive Survey

no code implementations4 Oct 2014 Nannan Wang, Xinbo Gao, DaCheng Tao, Xuelong. Li

CLM-based methods consist of a shape model and a number of local experts, each of which is utilized to detect a facial feature point.

3D FACE MODELING Face Alignment +2

Lazy Random Walks for Superpixel Segmentation

1 code implementation IEEE Trans. on Image Processing 2014 Jianbing Shen, Yunfan Du, Wenguan Wang, Xuelong. Li

Then, the boundaries of initial superpixels are obtained according to the probabilities and the commute time.


Compressed Hashing

no code implementations CVPR 2013 Yue Lin, Rong Jin, Deng Cai, Shuicheng Yan, Xuelong. Li

Recent studies have shown that hashing methods are effective for high dimensional nearest neighbor search.

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