Search Results for author: Liang Liu

Found 39 papers, 15 papers with code

面向对话文本的实体关系抽取(Entity Relation Extraction for Dialogue Text)

no code implementations CCL 2021 Liang Liu, Fang Kong

“实体关系抽取旨在从文本中抽取出实体之间的语义关系, 是自然语言处理的一项基本任务。在新闻报道、维基百科等规范文本上该任务的研究相对丰富, 已经取得了一定的效果, 但面向对话文本的相关研究还处于起始阶段。相较于规范文本, 用于实体关系抽取的对话语料规模较小, 对话文本的有效特征难以捕获, 这使得面向对话文本的实体关系抽取更具挑战。该文针对这一任务提出了一个基于Star-Transformer的实体关系抽取模型, 通过融入高速网络进行信息桥接, 并在此基础上融入交互信息和知识, 最后使用多任务学习机制进一步提升模型的性能。在DialogRE公开数据集上实验得到F1值为55. 7%, F1c值为52. 3%, 证明了提出方法的有效性。”

Relation Extraction

Networked Sensing in 6G Cellular Networks: Opportunities and Challenges

no code implementations1 Jun 2022 Liang Liu, Shuowen Zhang, Rui Du, Tong Xiao Han, Shuguang Cui

This article will discuss about the possibility of exploiting the future sixth-generation (6G) cellular network to realize ISAC.

Trilateration-Based Device-Free Sensing: Two Base Stations and One Passive IRS Are Sufficient

no code implementations25 May 2022 QiPeng Wang, Liang Liu, Shuowen Zhang, Francis C. M. Lau

The classic trilateration technique can localize each target based on its distances to three anchors with known coordinates.

Scalable Multi-view Clustering with Graph Filtering

1 code implementation18 May 2022 Liang Liu, Peng Chen, Guangchun Luo, Zhao Kang, Yonggang Luo, Sanchu Han

With the explosive growth of multi-source data, multi-view clustering has attracted great attention in recent years.

FRIH: Fine-grained Region-aware Image Harmonization

no code implementations13 May 2022 Jinlong Peng, Zekun Luo, Liang Liu, Boshen Zhang, Tao Wang, Yabiao Wang, Ying Tai, Chengjie Wang, Weiyao Lin

Image harmonization aims to generate a more realistic appearance of foreground and background for a composite image.

SDOAnet: An Efficient Deep Learning-Based DOA Estimation Network for Imperfect Array

1 code implementation19 Mar 2022 Peng Chen, Zhimin Chen, Liang Liu, Yun Chen, Xianbin Wang

Simulation results show that the proposed SDOAnet outperforms the existing DOA estimation methods with the effect of the imperfect array.

Super-Resolution

Exploiting Temporal Side Information in Massive IoT Connectivity

no code implementations5 Jan 2022 QiPeng Wang, Liang Liu, Shuowen Zhang, Francis C. M. Lau

In particular, we propose to leverage the temporal correlation in device activity, e. g., a device active in the previous coherence block is more likely to be still active in the current coherence block, to improve the detection and estimation performance.

Action Detection Activity Detection

Multilayer Graph Contrastive Clustering Network

no code implementations28 Dec 2021 Liang Liu, Zhao Kang, Ling Tian, Wenbo Xu, Xixu He

To this end, we propose a generic and effective autoencoder framework for multilayer graph clustering named Multilayer Graph Contrastive Clustering Network (MGCCN).

Graph Clustering

SelFSR: Self-Conditioned Face Super-Resolution in the Wild via Flow Field Degradation Network

no code implementations20 Dec 2021 Xianfang Zeng, Jiangning Zhang, Liang Liu, Guangzhong Tian, Yong liu

To tackle this problem, we propose a novel domain-adaptive degradation network for face super-resolution in the wild.

Super-Resolution

Detection of Abrupt Change in Channel Covariance Matrix for Multi-Antenna Communication

1 code implementation9 Sep 2021 Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang, Erik G. Larsson

This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.

Change Detection

LuMaMi28: Real-Time Millimeter-Wave Massive MIMO Systems with Antenna Selection

no code implementations7 Sep 2021 MinKeun Chung, Liang Liu, Andreas Johansson, Sara Gunnarsson, Martin Nilsson, Zhinong Ying, Olof Zander, Kamal Samanta, Chris Clifton, Toshiyuki Koimori, Shinya Morita, Satoshi Taniguchi, Fredrik Tufvesson, Ove Edfors

The UEs are equipped with a beam-switchable antenna array for real-time antenna selection where the one with the highest channel magnitude, out of four pre-defined beams, is selected.

Device-Free Sensing in OFDM Cellular Network

no code implementations20 Aug 2021 Qin Shi, Liang Liu, Shuowen Zhang, Shuguang Cui

A novel two-phase sensing framework is proposed to localize the passive targets that cannot transmit/receive reference signals to/from the base stations (BSs), where the ranges of the targets are estimated based on their reflected OFDM signals to the BSs in Phase I, and the location of each target is estimated based on its ranges to different BSs in Phase II.

A New Channel Estimation Strategy in Intelligent Reflecting Surface Assisted Networks

no code implementations22 Jun 2021 Rui Wang, Liang Liu, Shuowen Zhang, Changyuan Yu

Specifically, in Phase I, the correlation coefficients between the channels of a typical BS antenna and those of the other antennas are estimated; while in Phase II, the cascaded channel of the typical antenna is estimated.

DualGraph: A Graph-Based Method for Reasoning About Label Noise

no code implementations CVPR 2021 Haiyang Zhang, XiMing Xing, Liang Liu

Unreliable labels derived from large-scale dataset prevent neural networks from fully exploring the data.

Learning with noisy labels

Smoothed Multi-View Subspace Clustering

1 code implementation18 Jun 2021 Peng Chen, Liang Liu, Zhengrui Ma, Zhao Kang

In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views.

Multi-view Subspace Clustering

On Massive IoT Connectivity with Temporally-Correlated User Activity

1 code implementation27 Jan 2021 QiPeng Wang, Liang Liu, Shuowen Zhang, Francis C. M. Lau

In particular, we propose to leverage the temporal correlation in user activity, i. e., a device active at the previous time slot is more likely to be still active at the current moment, to improve the detection performance.

Action Detection Activity Detection Information Theory Signal Processing Information Theory

cross-modal knowledge enhancement mechanism for few-shot learning

no code implementations1 Jan 2021 Haiyang Zhang, Jiaming Duan, Liang Liu

After that, with the message-passing mechanism, CKEM selects and transfers relevant knowledge from external semantic knowledge bank to original visual-based class representations in Knowledge Fusion Model(KFM).

Few-Shot Learning

HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation

1 code implementation14 Dec 2020 Xiaoyang Lyu, Liang Liu, Mengmeng Wang, Xin Kong, Lina Liu, Yong liu, Xinxin Chen, Yi Yuan

To obtainmore accurate depth estimation in large gradient regions, itis necessary to obtain high-resolution features with spatialand semantic information.

Monocular Depth Estimation Self-Supervised Learning

Distributed and Scalable Uplink Processing for LIS: Algorithm, Architecture, and Design Trade-offs

no code implementations9 Dec 2020 Jesus Rodriguez Sanchez, Fredrik Rusek, Ove Edfors, Liang Liu

The Large Intelligent Surface (LIS) is a promising technology in the areas of wireless communication, remote sensing and positioning.

Millimeter-Wave Massive MIMO Testbed with Hybrid Beamforming

no code implementations2 Dec 2020 MinKeun Chung, Liang Liu, Andreas Johansson, Martin Nilsson, Olof Zander, Zhinong Ying, Fredrik Tufvesson, Ove Edfors

In this paper, we present a real-time mmWave (28 GHz) massive MIMO testbed with hybrid beamforming.

A Two-Stage Radar Sensing Approach based on MIMO-OFDM Technology

no code implementations12 Nov 2020 Liang Liu, Shuowen Zhang

Since the technologies of orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) are widely used in the legacy cellular systems, this paper proposes a two-stage signal processing approach for radar sensing in an MIMO-OFDM system, where the scattered channels caused by various targets are estimated in the first stage, and the location information of the targets is then extracted from their scattered channels in the second stage.

An Efficient Algorithm for Device Detection and Channel Estimation in Asynchronous IoT Systems

no code implementations20 Oct 2020 Liang Liu, Ya-Feng Liu

A great amount of endeavour has recently been devoted to the joint device activity detection and channel estimation problem in massive machine-type communications.

Action Detection Activity Detection

Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

1 code implementation ECCV 2020 Liang Liu, Hao Lu, Hongwei Zou, Haipeng Xiong, Zhiguo Cao, Chunhua Shen

Inspired by scale weighing, we propose a novel 'counting scale' termed LibraNet where the count value is analogized by weight.

Crowd Counting reinforcement-learning

A New Accelerated Stochastic Gradient Method with Momentum

no code implementations31 May 2020 Liang Liu, Xiaopeng Luo

In this paper, we propose a novel accelerated stochastic gradient method with momentum, which momentum is the weighted average of previous gradients.

Hierarchical and Efficient Learning for Person Re-Identification

no code implementations18 May 2020 Jiangning Zhang, Liang Liu, Chao Xu, Yong liu

Recent works in the person re-identification task mainly focus on the model accuracy while ignore factors related to the efficiency, e. g. model size and latency, which are critical for practical application.

Person Re-Identification

APB2Face: Audio-guided face reenactment with auxiliary pose and blink signals

2 code implementations30 Apr 2020 Jiangning Zhang, Liang Liu, Zhu-Cun Xue, Yong liu

Audio-guided face reenactment aims at generating photorealistic faces using audio information while maintaining the same facial movement as when speaking to a real person.

Face Reenactment

A Learning Framework for n-bit Quantized Neural Networks toward FPGAs

1 code implementation6 Apr 2020 Jun Chen, Liang Liu, Yong liu, Xianfang Zeng

Furthermore, we also design a shift vector processing element (SVPE) array to replace all 16-bit multiplications with SHIFT operations in convolution operation on FPGAs.

Extended Feature Pyramid Network for Small Object Detection

1 code implementation16 Mar 2020 Chunfang Deng, Mengmeng Wang, Liang Liu, Yong liu

Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.

object-detection Small Object Detection

Processing Distribution and Architecture Tradeoff for Large Intelligent Surface Implementation

no code implementations14 Jan 2020 Jesus Rodriguez Sanchez, Ove Edfors, Fredrik Rusek, Liang Liu

The Large Intelligent Surface (LIS) concept has emerged recently as a new paradigm for wireless communication, remote sensing and positioning.

From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting

3 code implementations7 Jan 2020 Haipeng Xiong, Hao Lu, Chengxin Liu, Liang Liu, Chunhua Shen, Zhiguo Cao

Visual counting, a task that aims to estimate the number of objects from an image/video, is an open-set problem by nature, i. e., the number of population can vary in [0, inf) in theory.

Object Counting

PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning

no code implementations19 Jun 2019 Guangyao Zhai, Liang Liu, Linjian Zhang, Yong liu

The feature-encoding module encodes the short-term motion feature in an image pair, while the memory-propagating module captures the long-term motion feature in the consecutive image pairs.

Camera Calibration Motion Estimation +2

FReeNet: Multi-Identity Face Reenactment

no code implementations CVPR 2020 Jiangning Zhang, Xianfang Zeng, Mengmeng Wang, Yusu Pan, Liang Liu, Yong liu, Yu Ding, Changjie Fan

This paper presents a novel multi-identity face reenactment framework, named FReeNet, to transfer facial expressions from an arbitrary source face to a target face with a shared model.

Face Reenactment

An efficient deep learning hashing neural network for mobile visual search

no code implementations21 Oct 2017 Heng Qi, Wu Liu, Liang Liu

Mobile visual search applications are emerging that enable users to sense their surroundings with smart phones.

On the evolution of word usage of classical Chinese poetry

no code implementations10 Sep 2015 Liang Liu, Lili Yu

The primary goal of this study is to provide quantitative evidence of the evolutionary linkages, with emphasis on character usage, among different period genres of classical Chinese poetry.

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