Search Results for author: Jie Liu

Found 72 papers, 18 papers with code

Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency Detection

1 code implementation ECCV 2020 Miao Zhang, Sun Xiao Fei, Jie Liu, Shuang Xu, Yongri Piao, Huchuan Lu

In this paper, we propose an asymmetric two-stream architecture taking account of the inherent differences between RGB and depth data for saliency detection.

Saliency Detection

AdaDM: Enabling Normalization for Image Super-Resolution

1 code implementation27 Nov 2021 Jie Liu, Jie Tang, Gangshan Wu

We found that the standard deviation of the residual feature shrinks a lot after normalization layers, which causes the performance degradation in SR networks.

Image Super-Resolution

Auto robust relative radiometric normalization via latent change noise modelling

no code implementations24 Nov 2021 Shiqi Liu, Lu Wang, Jie Lian, Ting Chen, Cong Liu, Xuchen Zhan, Jintao Lu, Jie Liu, Ting Wang, Dong Geng, Hongwei Duan, Yuze Tian

Relative radiometric normalization(RRN) of different satellite images of the same terrain is necessary for change detection, object classification/segmentation, and map-making tasks.

Object Classification

Approaching the Limit of Image Rescaling via Flow Guidance

no code implementations9 Nov 2021 Shang Li, GuiXuan Zhang, Zhengxiong Luo, Jie Liu, Zhi Zeng, Shuwu Zhang

In this paper, instead of directly applying the LR guidance, we propose an additional invertible flow guidance module (FGM), which can transform the downscaled representation to the visually plausible image during downscaling and transform it back during upscaling.

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans

no code implementations24 Sep 2021 Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee, Matthew Pastewait, Christian Piers, Jie Liu, Fang Wang, Li Wang, Christina Jackson, Wei-Lun Chao, Dinggang Shen, Ching-Chang Ko

Our TS-MDL first adopts an end-to-end \emph{i}MeshSegNet method (i. e., a variant of the existing MeshSegNet with both improved accuracy and efficiency) to label each tooth on the downsampled scan.

Edge-Cloud Collaborated Object Detection via Difficult-Case Discriminator

no code implementations29 Aug 2021 Zhiqiang Cao, Zhijun Li, Pan Heng, Yongrui Chen, Daqi Xie, Jie Liu

To address this challenge, we propose a small-big model framework that deploys a big model in the cloud and a small model on the edge devices.

Object Detection

Federated Learning with Dynamic Transformer for Text to Speech

no code implementations9 Jul 2021 Zhenhou Hong, Jianzong Wang, Xiaoyang Qu, Jie Liu, Chendong Zhao, Jing Xiao

Text to speech (TTS) is a crucial task for user interaction, but TTS model training relies on a sizable set of high-quality original datasets.

Federated Learning

From General to Specific: Online Updating for Blind Super-Resolution

no code implementations6 Jul 2021 Shang Li, GuiXuan Zhang, Zhengxiong Luo, Jie Liu, Zhi Zeng, Shuwu Zhang

It does not rely on predefined blur kernels and allows the model weights to be updated according to the degradation of the test image.


Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation

no code implementations CVPR 2021 Guo-Sen Xie, Jie Liu, Huan Xiong, Ling Shao

However, they fail to fully leverage the high-order appearance relationships between multi-scale features among the support-query image pairs, thus leading to an inaccurate localization of the query objects.

Few-Shot Semantic Segmentation Semantic Segmentation

Detecting and Correcting IMU Movements During Joint Angle Estimation

no code implementations9 Jun 2021 Chunzhi Yi, Feng Jiang, Baichun Wei, Chifu Yang, Zhen Ding, Jubo Jin, Jie Liu

The results demonstrate our method is a promising solution to detecting and correcting IMU movements during JAE.

Anchor-based Plain Net for Mobile Image Super-Resolution

1 code implementation20 May 2021 Zongcai Du, Jie Liu, Jie Tang, Gangshan Wu

Along with the rapid development of real-world applications, higher requirements on the accuracy and efficiency of image super-resolution (SR) are brought forward.

Image Super-Resolution Quantization

Underwater Target Recognition based on Multi-Decision LOFAR Spectrum Enhancement: A Deep Learning Approach

no code implementations26 Apr 2021 Jie Chen, Jie Liu, Chang Liu, Jian Zhang, Bing Han

To overcome this issue and to further improve the recognition performance, we adopt a deep learning approach for underwater target recognition and propose a LOFAR spectrum enhancement (LSE)-based underwater target recognition scheme, which consists of preprocessing, offline training, and online testing.

LAI Estimation of Cucumber Crop Based on Improved Fully Convolutional Network

no code implementations16 Apr 2021 Weiqi Shu, Ling Wang, Bolong Liu, Jie Liu

How to measure LAI accurately and efficiently is the key to the crop yield estimation problem.


Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction

2 code implementations13 Mar 2021 Shaowei Chen, Yu Wang, Jie Liu, Yuelin Wang

Aspect sentiment triplet extraction (ASTE), which aims to identify aspects from review sentences along with their corresponding opinion expressions and sentiments, is an emerging task in fine-grained opinion mining.

Aspect Sentiment Triplet Extraction Machine Reading Comprehension +1

M6: A Chinese Multimodal Pretrainer

no code implementations1 Mar 2021 Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.

Image Generation

Truncation-Free Matching System for Display Advertising at Alibaba

no code implementations18 Feb 2021 Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai, Xiaoqiang Zhu

When receiving a user request, matching system (i) finds the crowds that the user belongs to; (ii) retrieves all ads that have targeted those crowds.

Few-Shot Semantic Segmentation With Cyclic Memory Network

no code implementations ICCV 2021 Guo-Sen Xie, Huan Xiong, Jie Liu, Yazhou Yao, Ling Shao

Specifically, we first generate N pairs (key and value) of multi-resolution query features guided by the support feature and its mask.

Few-Shot Semantic Segmentation Semantic Segmentation

Colonoscopy Polyp Detection: Domain Adaptation From Medical Report Images to Real-time Videos

no code implementations31 Dec 2020 Zhi-Qin Zhan, Huazhu Fu, Yan-Yao Yang, Jingjing Chen, Jie Liu, Yu-Gang Jiang

However, there are several issues between the image-based training and video-based inference, including domain differences, lack of positive samples, and temporal smoothness.

Domain Adaptation

Inception Convolution with Efficient Dilation Search

1 code implementation CVPR 2021 Jie Liu, Chuming Li, Feng Liang, Chen Lin, Ming Sun, Junjie Yan, Wanli Ouyang, Dong Xu

To develop a practical method for learning complex inception convolution based on the data, a simple but effective search algorithm, referred to as efficient dilation optimization (EDO), is developed.

Human Detection Instance Segmentation +3

The item selection problem for user cold-start recommendation

no code implementations27 Oct 2020 Yitong Meng, Jie Liu, Xiao Yan, James Cheng

When a new user just signs up on a website, we usually have no information about him/her, i. e. no interaction with items, no user profile and no social links with other users.

Recommendation Systems

Adaptive Gradient Method with Resilience and Momentum

no code implementations21 Oct 2020 Jie Liu, Chen Lin, Chuming Li, Lu Sheng, Ming Sun, Junjie Yan, Wanli Ouyang

Several variants of stochastic gradient descent (SGD) have been proposed to improve the learning effectiveness and efficiency when training deep neural networks, among which some recent influential attempts would like to adaptively control the parameter-wise learning rate (e. g., Adam and RMSProp).

Progressive Defense Against Adversarial Attacks for Deep Learning as a Service in Internet of Things

no code implementations15 Oct 2020 Ling Wang, Cheng Zhang, Zejian Luo, ChenGuang Liu, Jie Liu, Xi Zheng, Athanasios Vasilakos

To reduce the computational cost without loss of generality, we present a defense strategy called a progressive defense against adversarial attacks (PDAAA) for efficiently and effectively filtering out the adversarial pixel mutations, which could mislead the neural network towards erroneous outputs, without a-priori knowledge about the attack type.

Residual Feature Distillation Network for Lightweight Image Super-Resolution

2 code implementations24 Sep 2020 Jie Liu, Jie Tang, Gangshan Wu

Thanks to FDC, we can rethink the information multi-distillation network (IMDN) and propose a lightweight and accurate SISR model called residual feature distillation network (RFDN).

Image Super-Resolution

Adaptive Neural Network-Based Approximation to Accelerate Eulerian Fluid Simulation

no code implementations26 Aug 2020 Wenqian Dong, Jie Liu, Zhen Xie, Dong Li

Evaluating with 20, 480 input problems, we show that Smartfluidnet achieves 1. 46x and 590x speedup comparing with a state-of-the-art neural network model and the original fluid simulation respectively on an NVIDIA Titan X Pascal GPU, while providing better simulation quality than the state-of-the-art model.

Poet: Product-oriented Video Captioner for E-commerce

1 code implementation16 Aug 2020 Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Jie Liu, Jingren Zhou, Hongxia Yang, Fei Wu

Then, based on the aspects of the video-associated product, we perform knowledge-enhanced spatial-temporal inference on those graphs for capturing the dynamic change of fine-grained product-part characteristics.

Video Captioning

Synchronous Double-channel Recurrent Network for Aspect-Opinion Pair Extraction

1 code implementation ACL 2020 Shaowei Chen, Jie Liu, Yu Wang, Wenzheng Zhang, Ziming Chi

The opinion entity extraction unit and the relation detection unit are developed as two channels to extract opinion entities and relations simultaneously.

Entity Extraction using GAN Opinion Mining +1

Residual Feature Aggregation Network for Image Super-Resolution

no code implementations CVPR 2020 Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu

To maximize the power of the RFA framework, we further propose an enhanced spatial attention (ESA) block to make the residual features to be more focused on critical spatial contents.

Image Super-Resolution

Deep Convolutional Neural Network-based Bernoulli Heatmap for Head Pose Estimation

no code implementations24 May 2020 Zhongxu Hu, Yang Xing, Chen Lv, Peng Hang, Jie Liu

This paper proposes a novel Bernoulli heatmap for head pose estimation from a single RGB image.

Head Pose Estimation

Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error

no code implementations12 May 2020 Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen Wright, David Page

We study the $L_1$-regularized maximum likelihood estimator/estimation (MLE) problem for discrete Markov random fields (MRFs), where efficient and scalable learning requires both sparse regularization and approximate inference.

A Comprehensive Survey of Grammar Error Correction

no code implementations2 May 2020 Yu Wang, Yuelin Wang, Jie Liu, Zhuo Liu

More importantly, we discuss four kinds of basic approaches, including statistical machine translation based approach, neural machine translation based approach, classification based approach and language model based approach, six commonly applied performance boosting techniques for GEC systems and two data augmentation methods.

Data Augmentation Language Modelling +2

Computational Performance of a Germline Variant Calling Pipeline for Next Generation Sequencing

no code implementations1 Apr 2020 Jie Liu, Xiaotian Wu, Kai Zhang, Bing Liu, Renyi Bao, Xiao Chen, Yiran Cai, Yiming Shen, Xinjun He, Jun Yan, Weixing Ji

With the booming of next generation sequencing technology and its implementation in clinical practice and life science research, the need for faster and more efficient data analysis methods becomes pressing in the field of sequencing.

InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining

no code implementations30 Mar 2020 Junyang Lin, An Yang, Yichang Zhang, Jie Liu, Jingren Zhou, Hongxia Yang

We pretrain the model with three pretraining tasks, including masked segment modeling (MSM), masked region modeling (MRM) and image-text matching (ITM); and finetune the model on a series of vision-and-language downstream tasks.

Image Retrieval Text Matching +1

FLAME: A Self-Adaptive Auto-labeling System for Heterogeneous Mobile Processors

no code implementations3 Mar 2020 Jie Liu, Jiawen Liu, Zhen Xie, Dong Li

How to accurately and efficiently label data on a mobile device is critical for the success of training machine learning models on mobile devices.

CTM: Collaborative Temporal Modeling for Action Recognition

no code implementations8 Feb 2020 Qian Liu, Tao Wang, Jie Liu, Yang Guan, Qi Bu, Longfei Yang

In order to learn powerful feature of videos, we propose a Collaborative Temporal Modeling (CTM) block (Figure 1) to learn temporal information for action recognition.

Action Recognition Video Understanding

iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention

no code implementations7 Feb 2020 Qian Liu, Dongyang Cai, Jie Liu, Nan Ding, Tao Wang

The standard non-local (NL) module is effective in aggregating frame-level features on the task of video classification but presents low parameters efficiency and high computational cost.

General Classification Video Classification

Flow Rate Control in Smart District Heating Systems Using Deep Reinforcement Learning

no code implementations1 Dec 2019 Tinghao Zhang, Jing Luo, Ping Chen, Jie Liu

At high latitudes, many cities adopt a centralized heating system to improve the energy generation efficiency and to reduce pollution.

Learning to Predict More Accurate Text Instances for Scene Text Detection

no code implementations18 Nov 2019 XiaoQian Li, Jie Liu, Shuwu Zhang, GuiXuan Zhang

At present, multi-oriented text detection methods based on deep neural network have achieved promising performances on various benchmarks.

Scene Text Scene Text Detection

Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction

no code implementations12 Nov 2019 Liangyi Kang, Jie Liu, Lingqiao Liu, Qinfeng Shi, Dan Ye

Thus, we propose to create auxiliary fact representations from charge definitions to augment fact descriptions representation.

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search

2 code implementations12 Nov 2019 Xinyan Dai, Xiao Yan, Kelvin K. W. Ng, Jie Liu, James Cheng

In this paper, we present a new angle to analyze the quantization error, which decomposes the quantization error into norm error and direction error.

Data Compression Quantization

Understanding and Improving Proximity Graph based Maximum Inner Product Search

no code implementations30 Sep 2019 Jie Liu, Xiao Yan, Xinyan Dai, Zhirong Li, James Cheng, Ming-Chang Yang

Then we explain the good performance of ip-NSW as matching the norm bias of the MIPS problem - large norm items have big in-degrees in the ip-NSW proximity graph and a walk on the graph spends the majority of computation on these items, thus effectively avoids unnecessary computation on small norm items.

Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization

1 code implementation1 Jul 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

In this work, we alleviate the NAS search cost down to less than 3 hours, while achieving state-of-the-art image classification results under mobile latency constraints.

Hyperparameter Optimization Image Classification +1

Performance Analysis and Characterization of Training Deep Learning Models on Mobile Devices

no code implementations10 Jun 2019 Jie Liu, Jiawen Liu, Wan Du, Dong Li

In this paper, we perform a variety of experiments on a representative mobile device (the NVIDIA TX2) to study the performance of training deep learning models.

Single-Path NAS: Device-Aware Efficient ConvNet Design

no code implementations10 May 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

Can we automatically design a Convolutional Network (ConvNet) with the highest image classification accuracy under the latency constraint of a mobile device?

General Classification Image Classification +1

Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours

4 code implementations5 Apr 2019 Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

Can we automatically design a Convolutional Network (ConvNet) with the highest image classification accuracy under the runtime constraint of a mobile device?

General Classification Image Classification +1

Rotated Feature Network for multi-orientation object detection

no code implementations23 Mar 2019 Zhixin Zhang, Xudong Chen, Jie Liu, Kaibo Zhou

General detectors follow the pipeline that feature maps extracted from ConvNets are shared between classification and regression tasks.

Classification General Classification +2

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

1 code implementation7 Jan 2019 Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang

In this work, we propose to train CNNs from images annotated with multiple tags, to enhance the quality of visual representation of the trained CNN model.

Image Classification Object Detection +3

Norm-Range Partition: A Universal Catalyst for LSH based Maximum Inner Product Search (MIPS)

1 code implementation22 Oct 2018 Xiao Yan, Xinyan Dai, Jie Liu, Kaiwen Zhou, James Cheng

Recently, locality sensitive hashing (LSH) was shown to be effective for MIPS and several algorithms including $L_2$-ALSH, Sign-ALSH and Simple-LSH have been proposed.

On the Acceleration of L-BFGS with Second-Order Information and Stochastic Batches

no code implementations14 Jul 2018 Jie Liu, Yu Rong, Martin Takac, Junzhou Huang

This paper proposes a framework of L-BFGS based on the (approximate) second-order information with stochastic batches, as a novel approach to the finite-sum minimization problems.

A Spatial and Temporal Features Mixture Model with Body Parts for Video-based Person Re-Identification

no code implementations3 Jul 2018 Jie Liu, Cheng Sun, Xiang Xu, Baomin Xu, Shuangyuan Yu

In this paper we propose a novel Spatial and Temporal Features Mixture Model (STFMM) based on convolutional neural network (CNN) and recurrent neural network (RNN), in which the human body is split into $N$ parts in horizontal direction so that we can obtain more specific features.

Video-Based Person Re-Identification

Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN

no code implementations10 Apr 2018 Yingqi Qu, Jie Liu, Liangyi Kang, Qinfeng Shi, Dan Ye

To preserve more original information, we propose an attentive recurrent neural network with similarity matrix based convolutional neural network (AR-SMCNN) model, which is able to capture comprehensive hierarchical information utilizing the advantages of both RNN and CNN.

Question Answering

MLE-induced Likelihood for Markov Random Fields

no code implementations27 Mar 2018 Jie Liu, Hao Zheng

Especially as the size of the MRF increases, both the numerical performance and the computational cost of our approach remain consistently satisfactory, whereas Laplace approximation deteriorates and pseudolikelihood becomes computationally unbearable.

Stochastic Recursive Gradient Algorithm for Nonconvex Optimization

no code implementations20 May 2017 Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takáč

In this paper, we study and analyze the mini-batch version of StochAstic Recursive grAdient algoritHm (SARAH), a method employing the stochastic recursive gradient, for solving empirical loss minimization for the case of nonconvex losses.

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient

no code implementations ICML 2017 Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takáč

In this paper, we propose a StochAstic Recursive grAdient algoritHm (SARAH), as well as its practical variant SARAH+, as a novel approach to the finite-sum minimization problems.

Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption

no code implementations16 Dec 2016 Jie Liu, Martin Takac

We propose a projected semi-stochastic gradient descent method with mini-batch for improving both the theoretical complexity and practical performance of the general stochastic gradient descent method (SGD).

Topic Aware Neural Response Generation

1 code implementation21 Jun 2016 Chen Xing, Wei Wu, Yu Wu, Jie Liu, YaLou Huang, Ming Zhou, Wei-Ying Ma

We consider incorporating topic information into the sequence-to-sequence framework to generate informative and interesting responses for chatbots.

Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

no code implementations16 Apr 2015 Jakub Konečný, Jie Liu, Peter Richtárik, Martin Takáč

Our method first performs a deterministic step (computation of the gradient of the objective function at the starting point), followed by a large number of stochastic steps.

mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

no code implementations17 Oct 2014 Jakub Konečný, Jie Liu, Peter Richtárik, Martin Takáč

Our method first performs a deterministic step (computation of the gradient of the objective function at the starting point), followed by a large number of stochastic steps.

Defuzzify firstly or finally: Dose it matter in fuzzy DEMATEL under uncertain environment?

no code implementations20 Mar 2014 Yunpeng Li, Ya Li, Jie Liu, Yong Deng

The results of defuzzification at the first step are not coincide with the results of defuzzification at the final step. It seems that the alternative is to defuzzification in the final step in fuzzy DEMATEL.

Decision Making

Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models

no code implementations NeurIPS 2013 Jie Liu, David Page

In large-scale applications of undirected graphical models, such as social networks and biological networks, similar patterns occur frequently and give rise to similar parameters.

A brief network analysis of Artificial Intelligence publication

no code implementations23 Nov 2013 Yunpeng Li, Jie Liu, Yong Deng

In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940.

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