Search Results for author: Liang Li

Found 55 papers, 24 papers with code

Rˆ3Net:Relation-embedded Representation Reconstruction Network for Change Captioning

1 code implementation EMNLP 2021 Yunbin Tu, Liang Li, Chenggang Yan, Shengxiang Gao, Zhengtao Yu

In this paper, we propose a Relation-embedded Representation Reconstruction Network (Rˆ3Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.

Unsupervised Coherent Video Cartoonization with Perceptual Motion Consistency

no code implementations2 Apr 2022 Zhenhuan Liu, Liang Li, Huajie Jiang, Xin Jin, Dandan Tu, Shuhui Wang, Zheng-Jun Zha

Furthermore, we devise the spatio-temporal correlative map as a style-independent, global-aware regularization on the perceptual motion consistency.

Optical Flow Estimation Style Transfer

FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset

1 code implementation26 Mar 2022 Lizhen Wang, ZhiYuan Chen, Tao Yu, Chenguang Ma, Liang Li, Yebin Liu

In the coarse module, we generate a base parametric model from large-scale RGB-D images, which is able to predict accurate rough 3D face models in different genders, ages, etc.

3D Face Reconstruction Face Model

Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment

1 code implementation6 Mar 2022 Jiayu Xiao, Liang Li, Chaofei Wang, Zheng-Jun Zha, Qingming Huang

A feasible solution is to start with a GAN well-trained on a large scale source domain and adapt it to the target domain with a few samples, termed as few shot generative model adaption.

Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification

no code implementations3 Mar 2022 Zhipeng Huang, Jiawei Liu, Liang Li, Kecheng Zheng, Zheng-Jun Zha

RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images.

Person Re-Identification

Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification

no code implementations3 Mar 2022 Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha

In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers as a dynamically self-refining Gaussian process to alleviate the bias to unseen domain for improving the generalization.

Generalizable Person Re-identification Representation Learning

Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text Representation

1 code implementation1 Mar 2022 Xiang Hu, Haitao Mi, Liang Li, Gerard de Melo

We propose to use a top-down parser as a model-based pruning method, which also enables parallel encoding during inference.

Language Modelling

Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking

2 code implementations CVPR 2020 Jin Gao, Yan Lu, Xiaojuan Qi, Yutong Kou, Bing Li, Liang Li, Shan Yu, Weiming Hu

In this paper, we propose a simple yet effective recursive least-squares estimator-aided online learning approach for few-shot online adaptation without requiring offline training.

Continual Learning One-Shot Learning +2

Calibrated Feature Decomposition for Generalizable Person Re-Identification

1 code implementation27 Nov 2021 Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha

The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.

Domain Generalization Generalizable Person Re-identification

R$^3$Net:Relation-embedded Representation Reconstruction Network for Change Captioning

1 code implementation20 Oct 2021 Yunbin Tu, Liang Li, Chenggang Yan, Shengxiang Gao, Zhengtao Yu

In this paper, we propose a Relation-embedded Representation Reconstruction Network (R$^3$Net) to explicitly distinguish the real change from the large amount of clutter and irrelevant changes.

Edge-featured Graph Neural Architecture Search

no code implementations3 Sep 2021 Shaofei Cai, Liang Li, Xinzhe Han, Zheng-Jun Zha, Qingming Huang

Recently, researchers study neural architecture search (NAS) to reduce the dependence of human expertise and explore better GNN architectures, but they over-emphasize entity features and ignore latent relation information concealed in the edges.

Neural Architecture Search

Multi-Modulation Network for Audio-Visual Event Localization

no code implementations26 Aug 2021 Hao Wang, Zheng-Jun Zha, Liang Li, Xuejin Chen, Jiebo Luo

We propose a novel MultiModulation Network (M2N) to learn the above correlation and leverage it as semantic guidance to modulate the related auditory, visual, and fused features.

audio-visual event localization

Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation

1 code implementation13 Jul 2021 Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian

Due to the domain discrepancy in visual domain adaptation, the performance of source model degrades when bumping into the high data density near decision boundary in target domain.

Domain Adaptation

Structured Multi-Level Interaction Network for Video Moment Localization via Language Query

no code implementations CVPR 2021 Hao Wang, Zheng-Jun Zha, Liang Li, Dong Liu, Jiebo Luo

In particular, for cross-modal interaction, we interact the sentence-level query with the whole moment while interact the word-level query with content and boundary, as in a coarse-to-fine manner.

Frame

TreeBERT: A Tree-Based Pre-Trained Model for Programming Language

1 code implementation26 May 2021 Xue Jiang, Zhuoran Zheng, Chen Lyu, Liang Li, Lei Lyu

In this paper, we present TreeBERT, a tree-based pre-trained model for improving programming language-oriented generation tasks.

Code Summarization Language Modelling +1

Improving Machine Learning-Based Modeling of Semiconductor Devices by Data Self-Augmentation

no code implementations25 May 2021 Zeheng Wang, Liang Li, Ross C. C. Leon, Arne Laucht

In the electronics industry, introducing Machine Learning (ML)-based techniques can enhance Technology Computer-Aided Design (TCAD) methods.

Comparing Representations in Tracking for Event Camera-based SLAM

1 code implementation20 Apr 2021 Jianhao Jiao, Huaiyang Huang, Liang Li, Zhijian He, Yilong Zhu, Ming Liu

This paper investigates two typical image-type representations for event camera-based tracking: time surface (TS) and event map (EM).

Rethinking Graph Neural Architecture Search from Message-passing

1 code implementation CVPR 2021 Shaofei Cai, Liang Li, Jincan Deng, Beichen Zhang, Zheng-Jun Zha, Li Su, Qingming Huang

Inspired by the strong searching capability of neural architecture search (NAS) in CNN, this paper proposes Graph Neural Architecture Search (GNAS) with novel-designed search space.

feature selection Neural Architecture Search

Dissecting Energy Budget of a Gamma-Ray Burst Fireball

no code implementations9 Feb 2021 Bing Zhang, Yu Wang, Liang Li

The jet composition and radiative efficiency of GRBs are poorly constrained from the data.

High Energy Astrophysical Phenomena

Manipulating the anisotropic phase separation in strained VO2 epitaxial films by nanoscale ion-implantation

no code implementations18 Jan 2021 Changlong Hu, Liang Li, Xiaolei Wen, Yuliang Chen, Bowen Li, Hui Ren, Shanguang Zhao, Chongwen Zou

Manipulating the strain induced poly-domains and phase transition in correlated oxide material are important for high performance devices fabrication.

Materials Science Strongly Correlated Electrons

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

no code implementations13 Jan 2021 Dian Shi, Liang Li, Rui Chen, Pavana Prakash, Miao Pan, Yuguang Fang

The continuous convergence of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over 5G+ mobile devices, which pushes AI functions to mobile devices and initiates a new era of on-device AI applications.

Federated Learning Quantization

To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices

no code implementations22 Dec 2020 Liang Li, Dian Shi, Ronghui Hou, Hui Li, Miao Pan, Zhu Han

Recent advances in machine learning, wireless communication, and mobile hardware technologies promisingly enable federated learning (FL) over massive mobile edge devices, which opens new horizons for numerous intelligent mobile applications.

Federated Learning

Energy Efficient Federated Learning over Heterogeneous Mobile Devices via Joint Design of Weight Quantization and Wireless Transmission

no code implementations21 Dec 2020 Rui Chen, Liang Li, Kaiping Xue, Chi Zhang, Miao Pan, Yuguang Fang

To address these challenges, in this paper, we attempt to take FL into the design of future wireless networks and develop a novel joint design of wireless transmission and weight quantization for energy efficient FL over mobile devices.

Edge-computing Federated Learning +1

Learning Better Representation for Tables by Self-Supervised Tasks

no code implementations15 Oct 2020 Liang Li, Can Ma, Yinliang Yue, Linjun Shou, Dayong Hu

Secondly, the target texts in training dataset may contain redundant information or facts do not exist in the input tables.

Table-to-Text Generation

TDRE: A Tensor Decomposition Based Approach for Relation Extraction

no code implementations15 Oct 2020 Bin-Bin Zhao, Liang Li, Hui-Dong Zhang

Extracting entity pairs along with relation types from unstructured texts is a fundamental subtask of information extraction.

Relation Classification Tensor Decomposition

Selective Information Passing for MR/CT Image Segmentation

1 code implementation10 Oct 2020 Qikui Zhu, Liang Li, Jiangnan Hao, Yunfei Zha, Yan Zhang, Yanxiang Cheng, Fei Liao, Pingxiang Li

However, not all the feature maps transmitted by those connections contribute positively to the network performance.

Medical Image Segmentation Tumor Segmentation

Artificial Lateral Line Based Relative State Estimation for Two Adjacent Robotic Fish

no code implementations23 Jun 2020 Xingwen Zheng, Wei Wang, Liang Li, Guangming Xie

Then four typical regression methods, including random forest algorithm, support vector regression, back propagation neural network, and multiple linear regression method are used for establishing regression models between the ALLS-measured HPVs and the relative states.

Delay-Aware Multi-Agent Reinforcement Learning for Cooperative and Competitive Environments

1 code implementation11 May 2020 Baiming Chen, Mengdi Xu, Zuxin Liu, Liang Li, Ding Zhao

We also test the proposed algorithm in traffic scenarios that require coordination of all autonomous vehicles to show the practical value of delay-awareness.

Autonomous Vehicles Multi-agent Reinforcement Learning +1

Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios

no code implementations14 Apr 2020 Baiming Chen, Xiang Chen, Wu Qiong, Liang Li

Results show that the adversarial scenarios generated by our method significantly degrade the performance of the tested vehicles.

Autonomous Driving reinforcement-learning

State-Relabeling Adversarial Active Learning

1 code implementation CVPR 2020 Beichen Zhang, Liang Li, Shijie Yang, Shuhui Wang, Zheng-Jun Zha, Qingming Huang

In this paper, we propose a state relabeling adversarial active learning model (SRAAL), that leverages both the annotation and the labeled/unlabeled state information for deriving the most informative unlabeled samples.

Active Learning

Real-world Person Re-Identification via Degradation Invariance Learning

no code implementations CVPR 2020 Yukun Huang, Zheng-Jun Zha, Xueyang Fu, Richang Hong, Liang Li

Person re-identification (Re-ID) in real-world scenarios usually suffers from various degradation factors, e. g., low-resolution, weak illumination, blurring and adverse weather.

Image Restoration Person Re-Identification +1

Secret Sharing based Secure Regressions with Applications

no code implementations10 Apr 2020 Chaochao Chen, Liang Li, Wenjing Fang, Jun Zhou, Li Wang, Lei Wang, Shuang Yang, Alex Liu, Hao Wang

Nowadays, the utilization of the ever expanding amount of data has made a huge impact on web technologies while also causing various types of security concerns.

Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

1 code implementation CVPR 2020 Shuhao Cui, Shuhui Wang, Junbao Zhuo, Liang Li, Qingming Huang, Qi Tian

We find by theoretical analysis that the prediction discriminability and diversity could be separately measured by the Frobenius-norm and rank of the batch output matrix.

Domain Adaptation

Secure Social Recommendation based on Secret Sharing

no code implementations6 Feb 2020 Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou

It is well known that social information, which is rich on social platforms such as Facebook, are useful to recommender systems.

Recommendation Systems

Meta-Learning PAC-Bayes Priors in Model Averaging

no code implementations24 Dec 2019 Yimin Huang, Weiran Huang, Liang Li, Zhenguo Li

In this paper, we mainly consider the scenario in which we have a common model set used for model averaging instead of selecting a single final model via a model selection procedure to account for this model's uncertainty to improve reliability and accuracy of inferences.

Meta-Learning Model Selection

Low rank tensor completion with sparse regularization in a transformed domain

no code implementations19 Nov 2019 Ping-Ping Wang, Liang Li, Guang-Hui Cheng

While the sparse regularizer is imposed by a $\ell_{1}$-norm in a discrete cosine transformation (DCT) domain, which can better employ the local sparse property of completed data.

Machine Discovery of Partial Differential Equations from Spatiotemporal Data

1 code implementation15 Sep 2019 Ye Yuan, Junlin Li, Liang Li, Frank Jiang, Xiuchuan Tang, Fumin Zhang, Sheng Liu, Jorge Goncalves, Henning U. Voss, Xiuting Li, Jürgen Kurths, Han Ding

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data.

Knowledge-guided Pairwise Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation5 Sep 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Li Su, Qingming Huang

Weakly supervised referring expression grounding (REG) aims at localizing the referential entity in an image according to linguistic query, where the mapping between the image region (proposal) and the query is unknown in the training stage.

Referring Expression Region Proposal

Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding

1 code implementation ICCV 2019 Xuejing Liu, Liang Li, Shuhui Wang, Zheng-Jun Zha, Dechao Meng, Qingming Huang

It builds the correspondence between image region proposal and query in an adaptive manner: adaptive grounding and collaborative reconstruction.

Referring Expression Region Proposal

Image Classification base on PCA of Multi-view Deep Representation

no code implementations12 Mar 2019 Yaoqi Sun, Liang Li, Liang Zheng, Ji Hu, Yatong Jiang, Chenggang Yan

In the age of information explosion, image classification is the key technology of dealing with and organizing a large number of image data.

Classification General Classification +1

Fast OBDD Reordering using Neural Message Passing on Hypergraph

no code implementations6 Nov 2018 Feifan Xu, Fei He, Enze Xie, Liang Li

Ordered binary decision diagrams (OBDDs) are an efficient data structure for representing and manipulating Boolean formulas.

A Self-Attentive Model with Gate Mechanism for Spoken Language Understanding

no code implementations EMNLP 2018 Changliang Li, Liang Li, Ji Qi

In this work, we propose a novel self-attentive model with gate mechanism to fully utilize the semantic correlation between slot and intent.

Automatic Speech Recognition Intent Detection +3

An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as An Example

no code implementations12 Sep 2018 Yuanzhe Yao, Zeheng Wang, Liang Li, Kun Lu, Runyu Liu, Zhiyuan Liu, Jing Yan

In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of proposed model are presented.

Image Prediction for Limited-angle Tomography via Deep Learning with Convolutional Neural Network

no code implementations29 Jul 2016 Hanming Zhang, Liang Li, Kai Qiao, Linyuan Wang, Bin Yan, Lei LI, Guoen Hu

The qualitative and quantitative evaluations of experimental results indicate that the proposed method show a stable and prospective performance on artifacts reduction and detail recovery for limited angle tomography.

Computed Tomography (CT)

Maximum Cohesive Grid of Superpixels for Fast Object Localization

no code implementations CVPR 2013 Liang Li, Wei Feng, Liang Wan, Jiawan Zhang

For this purpose, we aim at constructing maximum cohesive SP-grid, which is composed of real nodes, i. e. SPs, and dummy nodes that are meaningless in the image with only position-taking function in the grid.

Object Localization Superpixels

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