Search Results for author: Jian-Huang Lai

Found 58 papers, 17 papers with code

An Asymmetric Modeling for Action Assessment

no code implementations ECCV 2020 Jibin Gao, Wei-Shi Zheng, Jia-Hui Pan, Chengying Gao, Yao-Wei Wang, Wei Zeng, Jian-Huang Lai

However, existing methods for action assessment are mostly limited to individual actions, especially lacking modeling of the asymmetric relations among agents (e. g., between persons and objects); and this limitation undermines their ability to assess actions containing asymmetrically interactive motion patterns, since there always exists subordination between agents in many interactive actions.

Action Assessment

Adaptively-weighted Integral Space for Fast Multiview Clustering

no code implementations25 Aug 2022 Man-Sheng Chen, Tuo Liu, Chang-Dong Wang, Dong Huang, Jian-Huang Lai

In view of this, we propose an Adaptively-weighted Integral Space for Fast Multiview Clustering (AIMC) with nearly linear complexity.

Multiview Clustering

Image Clustering with Contrastive Learning and Multi-scale Graph Convolutional Networks

no code implementations14 Jul 2022 Yuanku Xu, Dong Huang, Chang-Dong Wang, Jian-Huang Lai

Specifically, with two random augmentations performed on each image, the backbone network with two weight-sharing views is utilized to learn the representations for the augmented samples, which are then fed to ISM and JC-SLIM for instance-level and cluster-level contrastive learning, respectively.

Contrastive Learning Deep Clustering +1

Vision Transformer for Contrastive Clustering

1 code implementation26 Jun 2022 Hua-Bao Ling, Bowen Zhu, Dong Huang, Ding-Hua Chen, Chang-Dong Wang, Jian-Huang Lai

Vision Transformer (ViT) has shown its advantages over the convolutional neural network (CNN) with its ability to capture global long-range dependencies for visual representation learning.

Contrastive Learning Deep Clustering +3

Strongly Augmented Contrastive Clustering

1 code implementation1 Jun 2022 Xiaozhi Deng, Dong Huang, Ding-Hua Chen, Chang-Dong Wang, Jian-Huang Lai

In this paper, we present an end-to-end deep clustering approach termed Strongly Augmented Contrastive Clustering (SACC), which extends the conventional two-augmentation-view paradigm to multiple views and jointly leverages strong and weak augmentations for strengthened deep clustering.

Contrastive Learning Deep Clustering +1

DeepCluE: Enhanced Image Clustering via Multi-layer Ensembles in Deep Neural Networks

no code implementations1 Jun 2022 Dong Huang, Ding-Hua Chen, Xiangji Chen, Chang-Dong Wang, Jian-Huang Lai

In light of this, this paper presents a Deep Clustering via Ensembles (DeepCluE) approach, which bridges the gap between deep clustering and ensemble clustering by harnessing the power of multiple layers in deep neural networks.

Contrastive Learning Deep Clustering +1

Fast Multi-view Clustering via Ensembles: Towards Scalability, Superiority, and Simplicity

no code implementations22 Mar 2022 Dong Huang, Chang-Dong Wang, Jian-Huang Lai

Then, a set of diversified base clusterings for different view groups are obtained via fast graph partitioning, which are further formulated into a unified bipartite graph for final clustering in the late-stage fusion.

graph partitioning

Improving Adversarially Robust Few-Shot Image Classification With Generalizable Representations

no code implementations CVPR 2022 Junhao Dong, YuAn Wang, Jian-Huang Lai, Xiaohua Xie

Extensive experiments show that our method can significantly outperform state-of-the-art adversarially robust FSIC methods on two standard benchmarks.

Classification Few-Shot Image Classification +1

Modeling 3D Layout for Group Re-Identification

1 code implementation CVPR 2022 Quan Zhang, Kaiheng Dang, Jian-Huang Lai, Zhanxiang Feng, Xiaohua Xie

To the best of our knowledge, 3DT is the first work to address GReID with 3D perspective, and the City1M is the currently largest dataset.

Predictive Feature Learning for Future Segmentation Prediction

no code implementations ICCV 2021 Zihang Lin, Jiangxin Sun, Jian-Fang Hu, QiZhi Yu, Jian-Huang Lai, Wei-Shi Zheng

In the latent feature learned by the autoencoder, global structures are enhanced and local details are suppressed so that it is more predictive.

Hybrid Dynamic-static Context-aware Attention Network for Action Assessment in Long Videos

1 code implementation13 Aug 2020 Ling-An Zeng, Fa-Ting Hong, Wei-Shi Zheng, Qi-Zhi Yu, Wei Zeng, Yao-Wei Wang, Jian-Huang Lai

However, most existing works focus only on video dynamic information (i. e., motion information) but ignore the specific postures that an athlete is performing in a video, which is important for action assessment in long videos.

Action Assessment Action Quality Assessment

Adaptive Interaction Modeling via Graph Operations Search

1 code implementation CVPR 2020 Haoxin Li, Wei-Shi Zheng, Yu Tao, Haifeng Hu, Jian-Huang Lai

We propose to search the network structures with differentiable architecture search mechanism, which learns to construct adaptive structures for different videos to facilitate adaptive interaction modeling.

Action Analysis

Machine Translation With Weakly Paired Documents

no code implementations IJCNLP 2019 Lijun Wu, Jinhua Zhu, Di He, Fei Gao, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

1) We provide a simple approach to mine implicitly bilingual sentence pairs from document pairs which can then be used as supervised training signals.

Translation Unsupervised Machine Translation

Exploiting Monolingual Data at Scale for Neural Machine Translation

no code implementations IJCNLP 2019 Lijun Wu, Yiren Wang, Yingce Xia, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

In this work, we study how to use both the source-side and target-side monolingual data for NMT, and propose an effective strategy leveraging both of them.

 Ranked #1 on Machine Translation on WMT2016 English-German (SacreBLEU metric, using extra training data)

Machine Translation NMT +1

Learnable Parameter Similarity

no code implementations27 Jul 2019 Guangcong Wang, Jian-Huang Lai, Wenqi Liang, Guangrun Wang

Most of the existing approaches focus on specific visual tasks while ignoring the relations between them.

Transfer Learning

A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification

no code implementations7 Jul 2019 Jiaxuan Zhuo, Jian-Huang Lai, Peijia Chen

In this paper, we design a teacher-student learning framework to learn an occlusion-robust model from the full-body person domain to the occluded person domain.

Person Re-Identification

Depth Growing for Neural Machine Translation

1 code implementation ACL 2019 Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

While very deep neural networks have shown effectiveness for computer vision and text classification applications, how to increase the network depth of neural machine translation (NMT) models for better translation quality remains a challenging problem.

Machine Translation NMT +3

EdMot: An Edge Enhancement Approach for Motif-aware Community Detection

2 code implementations30 May 2019 Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai

Based on the new edge set, the original connectivity structure of the input network is enhanced to generate a rewired network, whereby the motif-based higher-order structure is leveraged and the hypergraph fragmentation issue is well addressed.

Social and Information Networks Physics and Society 97R40

Discovering Underlying Person Structure Pattern with Relative Local Distance for Person Re-identification

1 code implementation29 Jan 2019 Guangcong Wang, Jian-Huang Lai, Zhenyu Xie, Xiaohua Xie

With the discovered underlying person structure, the RLD method builds a bridge between the global and local feature representation and thus improves the capacity of feature representation for person re-ID.

Person Re-Identification Representation Learning

DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

2 code implementations15 Jan 2019 Zhi-Hong Deng, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu

To solve this problem, many methods have been studied, which can be generally categorized into two types, i. e., representation learning-based CF methods and matching function learning-based CF methods.

Collaborative Filtering Recommendation Systems +1

Spatial-Temporal Person Re-identification

3 code implementations8 Dec 2018 Guangcong Wang, Jian-Huang Lai, Peigen Huang, Xiaohua Xie

In this paper, we propose a novel two-stream spatial-temporal person ReID (st-ReID) framework that mines both visual semantic information and spatial-temporal information.

Person Re-Identification

Enhanced Ensemble Clustering via Fast Propagation of Cluster-wise Similarities

no code implementations30 Oct 2018 Dong Huang, Chang-Dong Wang, Hongxing Peng, Jian-Huang Lai, Chee-Keong Kwoh

Upon the constructed graph, a transition probability matrix is defined, based on which the random walk process is conducted to propagate the graph structural information.

Association

Learning to Teach with Dynamic Loss Functions

no code implementations NeurIPS 2018 Lijun Wu, Fei Tian, Yingce Xia, Yang Fan, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

Different from typical learning settings in which the loss function of a machine learning model is predefined and fixed, in our framework, the loss function of a machine learning model (we call it student) is defined by another machine learning model (we call it teacher).

BIG-bench Machine Learning Image Classification +1

Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter

no code implementations EMNLP 2018 Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

Many previous works have discussed the relationship between error propagation and the \emph{accuracy drop} (i. e., the left part of the translated sentence is often better than its right part in left-to-right decoding models) problem.

Machine Translation Text Summarization +1

A Study of Reinforcement Learning for Neural Machine Translation

1 code implementation EMNLP 2018 Lijun Wu, Fei Tian, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

Recent studies have shown that reinforcement learning (RL) is an effective approach for improving the performance of neural machine translation (NMT) system.

Machine Translation NMT +2

Early action prediction by soft regression

no code implementations IEEE Transactions on Pattern Analysis and Machine Intelligence 2018 Jian-Fang Hu, Wei-Shi Zheng, Lianyang Ma, Gang Wang, Jian-Huang Lai, Jian-Guo Zhang

Our formulation of soft regression framework 1) overcomes a usual assumption in existing early action prediction systems that the progress level of on-going sequence is given in the testing stage; and 2) presents a theoretical framework to better resolve the ambiguity and uncertainty of subsequences at early performing stage.

Early Action Prediction regression +1

Interleaved Structured Sparse Convolutional Neural Networks

no code implementations CVPR 2018 Guotian Xie, Jingdong Wang, Ting Zhang, Jian-Huang Lai, Richang Hong, Guo-Jun Qi

In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels.

IGCV$2$: Interleaved Structured Sparse Convolutional Neural Networks

2 code implementations17 Apr 2018 Guotian Xie, Jingdong Wang, Ting Zhang, Jian-Huang Lai, Richang Hong, Guo-Jun Qi

In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels.

Occluded Person Re-identification

no code implementations9 Apr 2018 Jiaxuan Zhuo, Zeyu Chen, Jian-Huang Lai, Guangcong Wang

Person re-identification (re-id) suffers from a serious occlusion problem when applied to crowded public places.

Person Re-Identification

Learning View-Specific Deep Networks for Person Re-Identification

no code implementations30 Mar 2018 Zhanxiang Feng, Jian-Huang Lai, Xiaohua Xie

In recent years, a growing body of research has focused on the problem of person re-identification (re-id).

Person Re-Identification

Adversarial Attribute-Image Person Re-identification

no code implementations5 Dec 2017 Zhou Yin, Wei-Shi Zheng, An-Cong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue Huang, Jian-Huang Lai

While attributes have been widely used for person re-identification (Re-ID) which aims at matching the same person images across disjoint camera views, they are used either as extra features or for performing multi-task learning to assist the image-image matching task.

Multi-Task Learning Person Re-Identification

Toward Multidiversified Ensemble Clustering of High-Dimensional Data: From Subspaces to Metrics and Beyond

1 code implementation9 Oct 2017 Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Chee-Keong Kwoh

The rapid emergence of high-dimensional data in various areas has brought new challenges to current ensemble clustering research.

RGB-Infrared Cross-Modality Person Re-Identification

no code implementations ICCV 2017 Ancong Wu, Wei-Shi Zheng, Hong-Xing Yu, Shaogang Gong, Jian-Huang Lai

To that end, matching RGB images with infrared images is required, which are heterogeneous with very different visual characteristics.

Ranked #3 on Cross-Modal Person Re-Identification on SYSU-MM01 (mAP (All-search & Single-shot) metric)

Cross-Modality Person Re-identification Cross-Modal Person Re-Identification

Deep Growing Learning

no code implementations ICCV 2017 Guangcong Wang, Xiaohua Xie, Jian-Huang Lai, Jiaxuan Zhuo

A bottleneck of SSL is the overfitting problem when training over the limited labeled data, especially on a complex model like a deep neural network.

Motion-Appearance Interactive Encoding for Object Segmentation in Unconstrained Videos

no code implementations25 Jul 2017 Chunchao Guo, Jian-Huang Lai, Xiaohua Xie

We present a novel method of integrating motion and appearance cues for foreground object segmentation in unconstrained videos.

Graph Matching Object Localization +2

Adversarial Neural Machine Translation

no code implementations20 Apr 2017 Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jian-Huang Lai, Tie-Yan Liu

The goal of the adversary is to differentiate the translation result generated by the NMT model from that by human.

Machine Translation NMT +1

Robust Depth-based Person Re-identification

no code implementations28 Mar 2017 Ancong Wu, Wei-Shi Zheng, Jian-Huang Lai

More specifically, we exploit depth voxel covariance descriptor and further propose a locally rotation invariant depth shape descriptor called Eigen-depth feature to describe pedestrian body shape.

Person Re-Identification

Person Re-Identification by Camera Correlation Aware Feature Augmentation

no code implementations26 Mar 2017 Ying-Cong Chen, Xiatian Zhu, Wei-Shi Zheng, Jian-Huang Lai

The challenge of person re-identification (re-id) is to match individual images of the same person captured by different non-overlapping camera views against significant and unknown cross-view feature distortion.

Person Re-Identification

Jointly learning heterogeneous features for rgb-d activity recognition

no code implementations IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 39 , Issue: 11 , Nov. 1 2017 ) 2016 Jian-Fang Hu, Wei-Shi Zheng, Jian-Huang Lai, Jian-Guo Zhang

The proposed model formed in a unified framework is capable of: 1) jointly mining a set of subspaces with the same dimensionality to exploit latent shared features across different feature channels, 2) meanwhile, quantifying the shared and feature-specific components of features in the subspaces, and 3) transferring feature-specific intermediate transforms (i-transforms) for learning fusion of heterogeneous features across datasets.

Activity Recognition Human-Object Interaction Detection +2

Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation

no code implementations3 Aug 2016 Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen

Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick.

Ensemble Learning

Robust Ensemble Clustering Using Probability Trajectories

no code implementations3 Jun 2016 Dong Huang, Jian-Huang Lai, Chang-Dong Wang

To address these two limitations, in this paper, we propose a novel ensemble clustering approach based on sparse graph representation and probability trajectory analysis.

Locally Weighted Ensemble Clustering

no code implementations17 May 2016 Dong Huang, Chang-Dong Wang, Jian-Huang Lai

Although some efforts have been made to (globally) evaluate and weight the base clusterings, yet these methods tend to view each base clustering as an individual and neglect the local diversity of clusters inside the same base clustering.

Association

Partial Person Re-Identification

no code implementations ICCV 2015 Wei-Shi Zheng, Xiang Li, Tao Xiang, Shengcai Liao, Jian-Huang Lai, Shaogang Gong

We address a new partial person re-identification (re-id) problem, where only a partial observation of a person is available for matching across different non-overlapping camera views.

Person Re-Identification

Deep Ranking for Person Re-identification via Joint Representation Learning

no code implementations26 May 2015 Shi-Zhe Chen, Chun-Chao Guo, Jian-Huang Lai

This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems.

Feature Engineering Learning-To-Rank +2

Data-Driven Scene Understanding with Adaptively Retrieved Exemplars

no code implementations3 Feb 2015 Xionghao Liu, Wei Yang, Liang Lin, Qing Wang, Zhaoquan Cai, Jian-Huang Lai

In the first step, the references are selected by jointly matching their appearances with the target as well as the semantics (i. e. the assigned labels of the target and the references).

Scene Understanding Semantic Segmentation +1

Learning Contour-Fragment-based Shape Model with And-Or Tree Representation

no code implementations3 Feb 2015 Liang Lin, Xiaolong Wang, Wei Yang, Jian-Huang Lai

This paper proposes a simple yet effective method to learn the hierarchical object shape model consisting of local contour fragments, which represents a category of shapes in the form of an And-Or tree.

Edge Detection Model Optimization

Discriminatively Trained And-Or Graph Models for Object Shape Detection

no code implementations2 Feb 2015 Liang Lin, Xiaolong Wang, Wei Yang, Jian-Huang Lai

In this paper, we investigate a novel reconfigurable part-based model, namely And-Or graph model, to recognize object shapes in images.

object-detection Object Detection

Complex Background Subtraction by Pursuing Dynamic Spatio-Temporal Models

no code implementations2 Feb 2015 Liang Lin, Yuanlu Xu, Xiaodan Liang, Jian-Huang Lai

Although it has been widely discussed in video surveillance, background subtraction is still an open problem in the context of complex scenarios, e. g., dynamic backgrounds, illumination variations, and indistinct foreground objects.

Combining Multiple Clusterings via Crowd Agreement Estimation and Multi-Granularity Link Analysis

no code implementations6 May 2014 Dong Huang, Jian-Huang Lai, Chang-Dong Wang

We present the normalized crowd agreement index (NCAI) to evaluate the quality of base clusterings in an unsupervised manner and thus weight the base clusterings in accordance with their clustering validity.

Clustering Ensemble graph partitioning

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