Search Results for author: Xuelong Li

Found 88 papers, 25 papers with code

HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation

no code implementations25 Mar 2024 Linglin Jing, Yiming Ding, Yunpeng Gao, Zhigang Wang, Xu Yan, Dong Wang, Gerald Schaefer, Hui Fang, Bin Zhao, Xuelong Li

In this paper, we propose a novel hybrid pseudo-labeling framework for unsupervised event-based semantic segmentation, HPL-ESS, to alleviate the influence of noisy pseudo labels.

Image Reconstruction Segmentation +2

Deep Contrastive Graph Learning with Clustering-Oriented Guidance

no code implementations25 Feb 2024 Mulin Chen, Bocheng Wang, Xuelong Li

Graph Convolutional Network (GCN) has exhibited remarkable potential in improving graph-based clustering.

Clustering Contrastive Learning +1

Large-Scale Actionless Video Pre-Training via Discrete Diffusion for Efficient Policy Learning

no code implementations22 Feb 2024 Haoran He, Chenjia Bai, Ling Pan, Weinan Zhang, Bin Zhao, Xuelong Li

In the fine-tuning stage, we harness the imagined future videos to guide low-level action learning trained on a limited set of robot data.

QuanTest: Entanglement-Guided Testing of Quantum Neural Network Systems

1 code implementation20 Feb 2024 Jinjing Shi, Zimeng Xiao, Heyuan Shi, Yu Jiang, Xuelong Li

Subsequently, QuanTest formulates the problem of generating test inputs that maximize the quantum entanglement sufficiency and capture incorrect behaviors of the QNN system as a joint optimization problem and solves it in a gradient-based manner to generate quantum adversarial examples.

Motion-Aware Video Frame Interpolation

1 code implementation5 Feb 2024 Pengfei Han, Fuhua Zhang, Bin Zhao, Xuelong Li

Subsequently, a cross-scale motion structure is presented to estimate and refine intermediate flow maps by the extracted features.

Optical Flow Estimation Video Frame Interpolation

GQHAN: A Grover-inspired Quantum Hard Attention Network

no code implementations25 Jan 2024 Ren-xin Zhao, Jinjing Shi, Xuelong Li

In response to the dilemma of HAM and QML, a Grover-inspired Quantum Hard Attention Mechanism (GQHAM) consisting of a Flexible Oracle (FO) and an Adaptive Diffusion Operator (ADO) is proposed.

Binary Classification Hard Attention +1

NWPU-MOC: A Benchmark for Fine-grained Multi-category Object Counting in Aerial Images

1 code implementation19 Jan 2024 Junyu Gao, Liangliang Zhao, Xuelong Li

Considering the absence of a dataset for this task, a large-scale Dataset (NWPU-MOC) is collected, consisting of 3, 416 scenes with a resolution of 1024 $\times$ 1024 pixels, and well-annotated using 14 fine-grained object categories.

Object Object Counting

Community Detection in the Multi-View Stochastic Block Model

no code implementations17 Jan 2024 Yexin Zhang, Zhongtian Ma, Qiaosheng Zhang, Zhen Wang, Xuelong Li

This paper considers the problem of community detection on multiple potentially correlated graphs from an information-theoretical perspective.

Community Detection Stochastic Block Model

Frequency Domain Nuances Mining for Visible-Infrared Person Re-identification

no code implementations4 Jan 2024 Yukang Zhang, Yang Lu, Yan Yan, Hanzi Wang, Xuelong Li

Specifically, we propose a novel Frequency Domain Nuances Mining (FDNM) method to explore the cross-modality frequency domain information, which mainly includes an amplitude guided phase (AGP) module and an amplitude nuances mining (ANM) module.

Face Recognition Person Re-Identification

SMC-NCA: Semantic-guided Multi-level Contrast for Semi-supervised Temporal Action Segmentation

no code implementations19 Dec 2023 Feixiang Zhou, Zheheng Jiang, Huiyu Zhou, Xuelong Li

However, learning the representation of each frame by unsupervised contrastive learning for action segmentation remains an open and challenging problem.

Action Segmentation Contrastive Learning +2

DGNet: Dynamic Gradient-Guided Network for Water-Related Optics Image Enhancement

no code implementations12 Dec 2023 Jingchun Zhou, Zongxin He, Qiuping Jiang, Kui Jiang, Xianping Fu, Xuelong Li

To solve this issue, previous methods often idealize the degradation process, and neglect the impact of medium noise and object motion on the distribution of image features, limiting the generalization and adaptability of the model.

SSIM UIE

Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning

no code implementations12 Dec 2023 Jiawei Sun, Bin Zhao, Dong Wang, Zhigang Wang, Jie Zhang, Nektarios Koukourakis, Juergen W. Czarske, Xuelong Li

Quantitative phase imaging (QPI) through multi-core fibers (MCFs) has been an emerging in vivo label-free endoscopic imaging modality with minimal invasiveness.

Retrieval

A Novel Normalized-Cut Solver with Nearest Neighbor Hierarchical Initialization

no code implementations26 Nov 2023 Feiping Nie, Jitao Lu, Danyang Wu, Rong Wang, Xuelong Li

To address the problems, we propose a novel N-Cut solver designed based on the famous coordinate descent method.

Clustering

Eliminating Quantization Errors in Classification-Based Sound Source Localization

1 code implementation21 Nov 2023 Linfeng Feng, Xiao-Lei Zhang, Xuelong Li

To address this, we propose an Unbiased Label Distribution (ULD) to eliminate quantization error in training targets.

Classification Quantization +1

GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

no code implementations20 Nov 2023 Chi Yan, Delin Qu, Dong Wang, Dan Xu, Zhigang Wang, Bin Zhao, Xuelong Li

In this paper, we introduce $\textbf{GS-SLAM}$ that first utilizes 3D Gaussian representation in the Simultaneous Localization and Mapping (SLAM) system.

Pose Tracking Simultaneous Localization and Mapping

Implicit Event-RGBD Neural SLAM

no code implementations18 Nov 2023 Delin Qu, Chi Yan, Dong Wang, Jie Yin, Dan Xu, Bin Zhao, Xuelong Li

To address these challenges, we propose EN-SLAM, the first event-RGBD implicit neural SLAM framework, which effectively leverages the high rate and high dynamic range advantages of event data for tracking and mapping.

Discretize Relaxed Solution of Spectral Clustering via a Non-Heuristic Algorithm

1 code implementation19 Oct 2023 Hongyuan Zhang, Xuelong Li

Unfortunately, the goal of the existing methods is not to find a discrete solution that minimizes the original objective.

Clustering

Distance Weighted Trans Network for Image Completion

no code implementations11 Oct 2023 Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, Xuelong Li, Yue Lu

The challenge of image generation has been effectively modeled as a problem of structure priors or transformation.

Image Generation

Point-PEFT: Parameter-Efficient Fine-Tuning for 3D Pre-trained Models

4 code implementations4 Oct 2023 Yiwen Tang, Ray Zhang, Zoey Guo, Dong Wang, Zhigang Wang, Bin Zhao, Xuelong Li

To this end, we introduce Point-PEFT, a novel framework for adapting point cloud pre-trained models with minimal learnable parameters.

QKSAN: A Quantum Kernel Self-Attention Network

no code implementations25 Aug 2023 Ren-xin Zhao, Jinjing Shi, Xuelong Li

Self-Attention Mechanism (SAM) excels at distilling important information from the interior of data to improve the computational efficiency of models.

Binary Classification Computational Efficiency +1

Disentangled Contrastive Image Translation for Nighttime Surveillance

no code implementations11 Jul 2023 Guanzhou Lan, Bin Zhao, Xuelong Li

Targeting the surveillance scenes, we develop a disentangled representation, which is an auxiliary pretext task that separates surveillance scenes into the foreground and background with contrastive learning.

Contrastive Learning Translation

Sequential Attention Source Identification Based on Feature Representation

no code implementations28 Jun 2023 Dongpeng Hou, Zhen Wang, Chao GAO, Xuelong Li

Snapshot observation based source localization has been widely studied due to its accessibility and low cost.

Graph Attention

Hierarchical Matching and Reasoning for Multi-Query Image Retrieval

1 code implementation26 Jun 2023 Zhong Ji, Zhihao LI, Yan Zhang, Haoran Wang, Yanwei Pang, Xuelong Li

Afterwards, the VR module is developed to excavate the potential semantic correlations among multiple region-query pairs, which further explores the high-level reasoning similarity.

Image Retrieval Retrieval

Variational Positive-incentive Noise: How Noise Benefits Models

no code implementations13 Jun 2023 Hongyuan Zhang, Sida Huang, Xuelong Li

From the experiments, it is shown that the proposed VPN generator can improve the base models.

Variational Inference

Image Reconstruction for Accelerated MR Scan with Faster Fourier Convolutional Neural Networks

no code implementations5 Jun 2023 Xiaohan Liu, Yanwei Pang, Xuebin Sun, Yiming Liu, Yonghong Hou, ZhenChang Wang, Xuelong Li

To address this problem, we propose the following: (1) a novel convolutional operator called Faster Fourier Convolution (FasterFC) to replace the two consecutive convolution operations typically used in convolutional neural networks (e. g., U-Net, ResNet).

3D Reconstruction Image Reconstruction

Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning

1 code implementation NeurIPS 2023 Haoran He, Chenjia Bai, Kang Xu, Zhuoran Yang, Weinan Zhang, Dong Wang, Bin Zhao, Xuelong Li

Specifically, we propose Multi-Task Diffusion Model (\textsc{MTDiff}), a diffusion-based method that incorporates Transformer backbones and prompt learning for generative planning and data synthesis in multi-task offline settings.

Reinforcement Learning (RL)

On the Value of Myopic Behavior in Policy Reuse

no code implementations28 May 2023 Kang Xu, Chenjia Bai, Shuang Qiu, Haoran He, Bin Zhao, Zhen Wang, Wei Li, Xuelong Li

Leveraging learned strategies in unfamiliar scenarios is fundamental to human intelligence.

Imbalanced Aircraft Data Anomaly Detection

no code implementations17 May 2023 Hao Yang, Junyu Gao, Yuan Yuan, Xuelong Li

Anomaly detection in temporal data from sensors under aviation scenarios is a practical but challenging task: 1) long temporal data is difficult to extract contextual information with temporal correlation; 2) the anomalous data are rare in time series, causing normal/abnormal imbalance in anomaly detection, making the detector classification degenerate or even fail.

Anomaly Detection Time Series

Behavior Contrastive Learning for Unsupervised Skill Discovery

1 code implementation8 May 2023 Rushuai Yang, Chenjia Bai, Hongyi Guo, Siyuan Li, Bin Zhao, Zhen Wang, Peng Liu, Xuelong Li

Under mild assumptions, our objective maximizes the MI between different behaviors based on the same skill, which serves as an upper bound of the previous MI objective.

Continuous Control Contrastive Learning

Transformer-based stereo-aware 3D object detection from binocular images

no code implementations24 Apr 2023 Hanqing Sun, Yanwei Pang, Jiale Cao, Jin Xie, Xuelong Li

In this paper, we explore the model design of Transformers in binocular 3D object detection, focusing particularly on extracting and encoding the task-specific image correspondence information.

3D Object Detection Object +1

Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One

no code implementations20 Apr 2023 Hongyuan Zhang, Yanan Zhu, Xuelong Li

It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming.

Stochastic Optimization

VTAE: Variational Transformer Autoencoder with Manifolds Learning

1 code implementation3 Apr 2023 Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, DaCheng Tao, Xuelong Li

This weak projection, however, can be addressed by a Riemannian metric, and we show that geodesics computation and accurate interpolations between data samples on the Riemannian manifold can substantially improve the performance of deep generative models.

Representation Learning

Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction

1 code implementation ICCV 2023 Delin Qu, Yizhen Lao, Zhigang Wang, Dong Wang, Bin Zhao, Xuelong Li

This paper addresses the problem of rolling shutter correction in complex nonlinear and dynamic scenes with extreme occlusion.

Rolling Shutter Correction

ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidance

2 code implementations29 Mar 2023 Zoey Guo, Yiwen Tang, Ray Zhang, Dong Wang, Zhigang Wang, Bin Zhao, Xuelong Li

In this paper, we propose ViewRefer, a multi-view framework for 3D visual grounding exploring how to grasp the view knowledge from both text and 3D modalities.

Visual Grounding

Propagate And Calibrate: Real-time Passive Non-line-of-sight Tracking

no code implementations CVPR 2023 Yihao Wang, Zhigang Wang, Bin Zhao, Dong Wang, Mulin Chen, Xuelong Li

In contrast, we propose a purely passive method to track a person walking in an invisible room by only observing a relay wall, which is more in line with real application scenarios, e. g., security.

Fully Self-Supervised Depth Estimation from Defocus Clue

1 code implementation CVPR 2023 Haozhe Si, Bin Zhao, Dong Wang, Yunpeng Gao, Mulin Chen, Zhigang Wang, Xuelong Li

We show that our framework circumvents the needs for the depth and AIF image ground-truth, and receives superior predictions, thus closing the gap between the theoretical success of DFD works and their applications in the real world.

Depth Estimation

USER: Unified Semantic Enhancement with Momentum Contrast for Image-Text Retrieval

1 code implementation17 Jan 2023 Yan Zhang, Zhong Ji, Di Wang, Yanwei Pang, Xuelong Li

(2) It limits the scale of negative sample pairs by employing the mini-batch based end-to-end training mechanism.

Contrastive Learning Retrieval +3

ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding

no code implementations ICCV 2023 Zoey Guo, Yiwen Tang, Ray Zhang, Dong Wang, Zhigang Wang, Bin Zhao, Xuelong Li

In this paper, we propose ViewRefer, a multi-view framework for 3D visual grounding exploring how to grasp the view knowledge from both text and 3D modalities.

Visual Grounding

Positive-incentive Noise

no code implementations19 Dec 2022 Xuelong Li

After introducing the task entropy, the noise can be classified into two kinds, Positive-incentive noise (Pi-noise or $\pi$-noise) and pure noise, according to whether the noise can reduce the complexity of the task.

Multi-Task Learning

On the Global Solution of Soft k-Means

no code implementations7 Dec 2022 Feiping Nie, Hong Chen, Rong Wang, Xuelong Li

This paper presents an algorithm to solve the Soft k-Means problem globally.

Clustering

Counting Like Human: Anthropoid Crowd Counting on Modeling the Similarity of Objects

no code implementations2 Dec 2022 Qi Wang, Juncheng Wang, Junyu Gao, Yuan Yuan, Xuelong Li

The mainstream crowd counting methods regress density map and integrate it to obtain counting results.

Crowd Counting

Search to Pass Messages for Temporal Knowledge Graph Completion

1 code implementation30 Oct 2022 Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li

In particular, we develop a generalized framework to explore topological and temporal information in TKGs.

Link Prediction Neural Architecture Search +2

Deep Learning Based Two-dimensional Speaker Localization With Large Ad-hoc Microphone Arrays

no code implementations19 Oct 2022 Shupei Liu, Yijun Gong, Xiao-Lei Zhang, Xuelong Li

Specifically, a convolutional neural network is applied to each node to get the direction-of-arrival (DOA) estimation of speech sources.

Meta-Causal Feature Learning for Out-of-Distribution Generalization

no code implementations22 Aug 2022 Yuqing Wang, Xiangxian Li, Zhuang Qi, Jingyu Li, Xuelong Li, Xiangxu Meng, Lei Meng

Causal inference has become a powerful tool to handle the out-of-distribution (OOD) generalization problem, which aims to extract the invariant features.

Causal Inference Out-of-Distribution Generalization +1

Learning in Audio-visual Context: A Review, Analysis, and New Perspective

no code implementations20 Aug 2022 Yake Wei, Di Hu, Yapeng Tian, Xuelong Li

A comprehensive survey that can systematically organize and analyze studies of the audio-visual field is expected.

audio-visual learning Scene Understanding

Memorizing Complementation Network for Few-Shot Class-Incremental Learning

no code implementations11 Aug 2022 Zhong Ji, Zhishen Hou, Xiyao Liu, Yanwei Pang, Xuelong Li

Few-shot Class-Incremental Learning (FSCIL) aims at learning new concepts continually with only a few samples, which is prone to suffer the catastrophic forgetting and overfitting problems.

Few-Shot Class-Incremental Learning Incremental Learning +1

Low-Light Hyperspectral Image Enhancement

1 code implementation5 Aug 2022 Xuelong Li, Guanlin Li, Bin Zhao

The illumination enhancement branch is adopted to enlighten the low-frequency component with reduced resolution.

Image Enhancement

Deep Manifold Learning with Graph Mining

no code implementations18 Jul 2022 Xuelong Li, Ziheng Jiao, Hongyuan Zhang, Rui Zhang

Admittedly, Graph Convolution Network (GCN) has achieved excellent results on graph datasets such as social networks, citation networks, etc.

Graph Mining

QSAN: A Near-term Achievable Quantum Self-Attention Network

no code implementations14 Jul 2022 Jinjing Shi, Ren-xin Zhao, Wenxuan Wang, Shichao Zhang, Xuelong Li

Self-Attention Mechanism (SAM) is good at capturing the internal connections of features and greatly improves the performance of machine learning models, espeacially requiring efficient characterization and feature extraction of high-dimensional data.

Binary Classification Image Classification +3

Spatio-temporal Gait Feature with Global Distance Alignment

no code implementations7 Mar 2022 Yifan Chen, Yang Zhao, Xuelong Li

In this paper, we try to enhance the discrimination of spatio-temporal gait features from two aspects: effective extraction of spatio-temporal gait features and reasonable refinement of extracted features.

Gait Recognition

Matrix Completion via Non-Convex Relaxation and Adaptive Correlation Learning

no code implementations4 Mar 2022 Xuelong Li, Hongyuan Zhang, Rui Zhang

We theoretically validate that it is equivalent to the existing matrix completion models.

Matrix Completion

Relation Regularized Scene Graph Generation

no code implementations22 Feb 2022 Yuyu Guo, Lianli Gao, Jingkuan Song, Peng Wang, Nicu Sebe, Heng Tao Shen, Xuelong Li

Inspired by this observation, in this article, we propose a relation regularized network (R2-Net), which can predict whether there is a relationship between two objects and encode this relation into object feature refinement and better SGG.

Graph Classification Graph Generation +6

New Tight Relaxations of Rank Minimization for Multi-Task Learning

no code implementations9 Dec 2021 Wei Chang, Feiping Nie, Rong Wang, Xuelong Li

Multi-task learning has been observed by many researchers, which supposes that different tasks can share a low-rank common yet latent subspace.

Multi-Task Learning

Adaptive Shrink-Mask for Text Detection

no code implementations18 Nov 2021 Chuang Yang, Mulin Chen, Yuan Yuan, Qi Wang, Xuelong Li

It weakens the coupling of texts to shrink-masks, which improves the robustness of detection results.

Text Detection

AnchorGAE: General Data Clustering via $O(n)$ Bipartite Graph Convolution

no code implementations12 Nov 2021 Hongyuan Zhang, Jiankun Shi, Rui Zhang, Xuelong Li

The core problems mainly come from two aspects: (1) the graph is unavailable in the most clustering scenes so that how to construct high-quality graphs on the non-graph data is usually the most important part; (2) given n samples, the graph-based clustering methods usually consume at least $\mathcal O(n^2)$ time to build graphs and the graph convolution requires nearly $\mathcal O(n^2)$ for a dense graph and $\mathcal O(|\mathcal{E}|)$ for a sparse one with $|\mathcal{E}|$ edges.

Clustering

LDC-Net: A Unified Framework for Localization, Detection and Counting in Dense Crowds

no code implementations10 Oct 2021 Qi Wang, Tao Han, Junyu Gao, Yuan Yuan, Xuelong Li

The rapid development in visual crowd analysis shows a trend to count people by positioning or even detecting, rather than simply summing a density map.

Visual Crowd Analysis

Hierarchical Multimodal Transformer to Summarize Videos

no code implementations22 Sep 2021 Bin Zhao, Maoguo Gong, Xuelong Li

To integrate the two kinds of information, they are encoded in a two-stream scheme, and a multimodal fusion mechanism is developed based on the hierarchical transformer.

Machine Translation Translation +2

Unsupervised Domain Adaptive Learning via Synthetic Data for Person Re-identification

no code implementations12 Sep 2021 Qi Wang, Sikai Bai, Junyu Gao, Yuan Yuan, Xuelong Li

In addition, due to domain gaps between different datasets, the performance is dramatically decreased when re-ID models pre-trained on label-rich datasets (source domain) are directly applied to other unlabeled datasets (target domain).

Person Re-Identification Unsupervised Domain Adaptation

Congested Crowd Instance Localization with Dilated Convolutional Swin Transformer

1 code implementation2 Aug 2021 Junyu Gao, Maoguo Gong, Xuelong Li

To this end, we propose a Dilated Convolutional Swin Transformer (DCST) for congested crowd scenes.

Crowd Counting Representation Learning

Deep Contrastive Graph Representation via Adaptive Homotopy Learning

no code implementations17 Jun 2021 Rui Zhang, Chengjun Lu, Ziheng Jiao, Xuelong Li

In particular, in this paper, we apply AH to contrastive learning (AHCL) such that it can be effectively transferred from weak-supervised learning (given label priori) to unsupervised learning, where soft labels of contrastive learning are directly and adaptively learned.

Contrastive Learning

Non-Gradient Manifold Neural Network

no code implementations15 Jun 2021 Rui Zhang, Ziheng Jiao, Hongyuan Zhang, Xuelong Li

Moreover, by unifying the flexible Stiefel manifold and adaptive support vector machine, we devise the novel decision layer which efficiently fits the manifold structure of the data and label information.

EA-Net: Edge-Aware Network for Flow-based Video Frame Interpolation

no code implementations17 May 2021 Bin Zhao, Xuelong Li

Specifically, in the flow estimation stage, three edge-aware mechanisms are developed to emphasize the frame edges in estimating flow maps, so that the edge-maps are taken as the auxiliary information to provide more guidance to boost the flow accuracy.

Video Frame Interpolation

AudioVisual Video Summarization

no code implementations17 May 2021 Bin Zhao, Maoguo Gong, Xuelong Li

Motivated by this, we propose to jointly exploit the audio and visual information for the video summarization task, and develop an AudioVisual Recurrent Network (AVRN) to achieve this.

Video Summarization

Reconstructive Sequence-Graph Network for Video Summarization

no code implementations10 May 2021 Bin Zhao, Haopeng Li, Xiaoqiang Lu, Xuelong Li

Then, the videos are summarized by exploiting both the local and global dependencies among shots.

Video Summarization

Spatial-Spectral Clustering with Anchor Graph for Hyperspectral Image

no code implementations24 Apr 2021 Qi Wang, Yanling Miao, Mulin Chen, Xuelong Li

In order to better handle the high dimensionality problem and preserve the spatial structures, this paper proposes a novel unsupervised approach called spatial-spectral clustering with anchor graph (SSCAG) for HSI data clustering.

Clustering

Auto-weighted Multi-view Feature Selection with Graph Optimization

no code implementations11 Apr 2021 Qi Wang, Xu Jiang, Mulin Chen, Xuelong Li

In this paper, we focus on the unsupervised multi-view feature selection which tries to handle high dimensional data in the field of multi-view learning.

feature selection Graph Learning +1

Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning

no code implementations25 Mar 2021 Yanling Miao, Qi Wang, Mulin Chen, Xuelong Li

Graph-based semi-supervised learning methods, which deal well with the situation of limited labeled data, have shown dominant performance in practical applications.

Descriptive Ensemble Learning +2

Feature Weighted Non-negative Matrix Factorization

no code implementations24 Mar 2021 Mulin Chen, Maoguo Gong, Xuelong Li

Non-negative Matrix Factorization (NMF) is one of the most popular techniques for data representation and clustering, and has been widely used in machine learning and data analysis.

Clustering

Entropy Minimizing Matrix Factorization

no code implementations24 Mar 2021 Mulin Chen, Xuelong Li

Considering that the outliers are usually much less than the normal samples, a new entropy loss function is established for matrix factorization, which minimizes the entropy of the residue distribution and allows a few samples to have large approximation errors.

Clustering

Enhanced Principal Component Analysis under A Collaborative-Robust Framework

no code implementations22 Mar 2021 Rui Zhang, Hongyuan Zhang, Xuelong Li

Principal component analysis (PCA) frequently suffers from the disturbance of outliers and thus a spectrum of robust extensions and variations of PCA have been developed.

Clustering

Multi-channel Deep Supervision for Crowd Counting

no code implementations17 Mar 2021 Bo Wei, Mulin Chen, Qi Wang, Xuelong Li

To obtain the accurate supervision information of different channels, the MDSNet employs an auxiliary network called SupervisionNet (SN) to generate abundant supervision maps based on existing groundtruth.

Crowd Counting

Weather GAN: Multi-Domain Weather Translation Using Generative Adversarial Networks

no code implementations9 Mar 2021 Xuelong Li, Kai Kou, Bin Zhao

To this end, the generator of Weather GAN is composed of an initial translation module, an attention module and a weather-cue segmentation module.

Style Transfer Translation

Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery

no code implementations6 Jan 2021 Rong Wang, Yihang Lu, Qianrong Zhang, Feiping Nie, Zhen Wang, Xuelong Li

To alleviate this problem, we proposed a novel ensemble and random collaborative representation-based detector (ERCRD) for HAD, which comprises two closely related stages.

Anomaly Detection Ensemble Learning

Sparse PCA via $l_{2,p}$-Norm Regularization for Unsupervised Feature Selection

no code implementations29 Dec 2020 Zhengxin Li, Feiping Nie, Jintang Bian, Xuelong Li

However, real-world data contain a large number of noise samples and features, making the similarity matrix constructed by original data cannot be completely reliable.

feature selection

Learning Independent Instance Maps for Crowd Localization

1 code implementation8 Dec 2020 Junyu Gao, Tao Han, Qi Wang, Yuan Yuan, Xuelong Li

Furthermore, to improve the segmentation quality for different density regions, we present a differentiable Binarization Module (BM) to output structured instance maps.

Binarization Segmentation

Learning Feature Sparse Principal Subspace

1 code implementation NeurIPS 2020 Lai Tian, Feiping Nie, Rong Wang, Xuelong Li

This paper presents new algorithms to solve the feature-sparsity constrained PCA problem (FSPCA), which performs feature selection and PCA simultaneously.

Dimensionality Reduction feature selection

Efficient Clustering Based On A Unified View Of $K$-means And Ratio-cut

1 code implementation NeurIPS 2020 Shenfei Pei, Feiping Nie, Rong Wang, Xuelong Li

In particular, over 15x and 7x speed-up can be obtained with respect to $k$-means on the synthetic dataset of 1 million samples and the benchmark dataset (CelebA) of 200k samples, respectively [GitHub].

Clustering

Muti-view Mouse Social Behaviour Recognition with Deep Graphical Model

1 code implementation4 Nov 2020 Zheheng Jiang, Feixiang Zhou, Aite Zhao, Xin Li, Ling Li, DaCheng Tao, Xuelong Li, Huiyu Zhou

To address this problem, we here propose a novel multiview latent-attention and dynamic discriminative model that jointly learns view-specific and view-shared sub-structures, where the former captures unique dynamics of each view whilst the latter encodes the interaction between the views.

Embedding Graph Auto-Encoder for Graph Clustering

no code implementations20 Feb 2020 Hongyuan Zhang, Rui Zhang, Xuelong Li

Driven by theoretical analysis about relaxed k-means, we design a specific GAE-based model for graph clustering to be consistent with the theory, namely Embedding Graph Auto-Encoder (EGAE).

Clustering Graph Clustering

Low Rank Regularization: A Review

no code implementations14 Aug 2018 Zhanxuan Hu, Feiping Nie, Rong Wang, Xuelong Li

Low rank regularization, in essence, involves introducing a low rank or approximately low rank assumption for matrix we aim to learn, which has achieved great success in many fields including machine learning, data mining and computer version.

BIG-bench Machine Learning Image Denoising

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