Search Results for author: Liang Liu

Found 76 papers, 31 papers with code

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 +2

Rethinking Mobile Block for Efficient Attention-based Models

1 code implementation ICCV 2023 Jiangning Zhang, Xiangtai Li, Jian Li, Liang Liu, Zhucun Xue, Boshen Zhang, Zhengkai Jiang, Tianxin Huang, Yabiao Wang, Chengjie Wang

This paper focuses on developing modern, efficient, lightweight models for dense predictions while trading off parameters, FLOPs, and performance.

Unity

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

FReeNet: Multi-Identity Face Reenactment

1 code implementation 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

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

3 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

AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model

1 code implementation10 Dec 2023 Teng Hu, Jiangning Zhang, Ran Yi, Yuzhen Du, Xu Chen, Liang Liu, Yabiao Wang, Chengjie Wang

Existing anomaly inspection methods are limited in their performance due to insufficient anomaly data.

Image Generation

Phasic Content Fusing Diffusion Model with Directional Distribution Consistency for Few-Shot Model Adaption

1 code implementation ICCV 2023 Teng Hu, Jiangning Zhang, Liang Liu, Ran Yi, Siqi Kou, Haokun Zhu, Xu Chen, Yabiao Wang, Chengjie Wang, Lizhuang Ma

To address these problems, we propose a novel phasic content fusing few-shot diffusion model with directional distribution consistency loss, which targets different learning objectives at distinct training stages of the diffusion model.

Domain Adaptation

A Mask Free Neural Network for Monaural Speech Enhancement

1 code implementation7 Jun 2023 Liang Liu, Haixin Guan, Jinlong Ma, Wei Dai, Guangyong Wang, Shaowei Ding

In speech enhancement, the lack of clear structural characteristics in the target speech phase requires the use of conservative and cumbersome network frameworks.

Speech Enhancement

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 object-detection +1

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

2 code implementations19 Mar 2022 Peng Chen, Zhimin Chen, Liang Liu, Yun Chen, Xianbin Wang

The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems.

Super-Resolution

Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region

2 code implementations7 Sep 2023 Teng Hu, Ran Yi, Haokun Zhu, Liang Liu, Jinlong Peng, Yabiao Wang, Chengjie Wang, Lizhuang Ma

To solve the problem, we propose Compositional Neural Painter, a novel stroke-based rendering framework which dynamically predicts the next painting region based on the current canvas, instead of dividing the image plane uniformly into painting regions.

Style Transfer

Toward High Quality Facial Representation Learning

1 code implementation7 Sep 2023 Yue Wang, Jinlong Peng, Jiangning Zhang, Ran Yi, Liang Liu, Yabiao Wang, Chengjie Wang

To improve the facial representation quality, we use feature map of a pre-trained visual backbone as a supervision item and use a partially pre-trained decoder for mask image modeling.

Contrastive Learning Face Alignment +2

Spacecraft Anomaly Detection with Attention Temporal Convolution Network

1 code implementation13 Mar 2023 Liang Liu, Ling Tian, Zhao Kang, Tianqi Wan

The time series telemetry data generated by on-orbit spacecraft \textcolor{blue}{contains} important information about the status of spacecraft.

Anomaly Detection Graph Attention +2

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

Exploiting Temporal Side Information in Massive IoT Connectivity

1 code implementation5 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

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.

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.

Clustering Multi-view Subspace Clustering

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

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.

Attribute Clustering

Learning with Noisy labels via Self-supervised Adversarial Noisy Masking

1 code implementation CVPR 2023 Yuanpeng Tu, Boshen Zhang, Yuxi Li, Liang Liu, Jian Li, Jiangning Zhang, Yabiao Wang, Chengjie Wang, Cai Rong Zhao

Collecting large-scale datasets is crucial for training deep models, annotating the data, however, inevitably yields noisy labels, which poses challenges to deep learning algorithms.

Ranked #2 on Image Classification on Clothing1M (using extra training data)

Learning with noisy labels

Calibrated Teacher for Sparsely Annotated Object Detection

1 code implementation14 Mar 2023 Haohan Wang, Liang Liu, Boshen Zhang, Jiangning Zhang, Wuhao Zhang, Zhenye Gan, Yabiao Wang, Chengjie Wang, Haoqian Wang

Recent works on sparsely annotated object detection alleviate this problem by generating pseudo labels for the missing annotations.

Object object-detection +2

Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes

1 code implementation14 Feb 2023 Yuanpeng Tu, Yuxi Li, Boshen Zhang, Liang Liu, Jiangning Zhang, Yabiao Wang, Cai Rong Zhao

Based on the proposed estimators, we devise an adaptive self-supervised training framework, which exploits the contextual reliance and estimated likelihood to refine mask annotations in anomaly areas.

Anomaly Detection Autonomous Driving

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.

Deep Hashing

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.

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

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

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.

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

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

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.

Vocal Bursts Valence Prediction

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.

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.

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.

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.

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.

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

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

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).

Clustering Graph Clustering

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.

Image Harmonization

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.

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.

Detecting Abrupt Changes in Channel Covariance Matrix for MIMO Communication

no code implementations5 Jul 2022 Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang, Erik G. Larsson

Our paper aims to adopt the classic change detection theory to detect the change in the channel covariance matrix as accurately and quickly as possible such that the new covariance matrix can be re-estimated in time.

Change Detection

Intelligent Omni-Surfaces Aided Wireless Communications: Does the Reciprocity Hold?

no code implementations6 Nov 2022 Shaohua Yue, Shuhao Zeng, Hongliang Zhang, Fenghan Lin, Liang Liu, Boya Di

Intelligent omni-surfaces (IOS) have attracted great attention recently due to its potential to achieve full-dimensional communications by simultaneously reflecting and refracting signals toward both sides of the surface.

Open-Ended Question Answering

The LuViRA Dataset: Measurement Description

no code implementations10 Feb 2023 Ilayda Yaman, Guoda Tian, Martin Larsson, Patrik Persson, Michiel Sandra, Alexander Dürr, Erik Tegler, Nikhil Challa, Henrik Garde, Fredrik Tufvesson, Kalle Åström, Ove Edfors, Steffen Malkowsky, Liang Liu

We present a dataset to evaluate localization algorithms, which utilizes vision, audio, and radio sensors: the Lund University Vision, Radio, and Audio (LuViRA) Dataset.

Image Classification

Joint Data Association, NLOS Mitigation, and Clutter Suppression for Networked Device-Free Sensing in 6G Cellular Network

no code implementations16 Feb 2023 Qin Shi, Liang Liu, Shuowen Zhang

Recently, there is a growing interest in achieving integrated sensing and communication (ISAC) in the sixth-generation (6G) cellular network.

A Heterogeneous 6G Networked Sensing Architecture with Active and Passive Anchors

no code implementations4 May 2023 QiPeng Wang, Liang Liu, Shuowen Zhang, Boya Di, Francis C. M. Lau

In this paper, we show that the distance between a target and its associated IRS can be indirectly estimated based on the length of the BS-target-BS path and the BS-target-IRS-BS path.

Long-Term Value of Exploration: Measurements, Findings and Algorithms

no code implementations12 May 2023 Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen

We conduct live experiments on one of the largest short-form video recommendation platforms that serves billions of users to validate the new experiment designs, quantify the long-term values of exploration, and to verify the effectiveness of the adopted neural linear bandit algorithm for exploration.

Recommendation Systems

Dual Path Transformer with Partition Attention

no code implementations24 May 2023 Zhengkai Jiang, Liang Liu, Jiangning Zhang, Yabiao Wang, Mingang Chen, Chengjie Wang

This paper introduces a novel attention mechanism, called dual attention, which is both efficient and effective.

Image Classification object-detection +2

A Quantize-then-Estimate Protocol for CSI Acquisition in IRS-Aided Downlink Communication

no code implementations4 Aug 2023 Rui Wang, Zhaorui Wang, Liang Liu, Shuowen Zhang, Shi Jin

Different from the uplink counterpart where the BS possesses the pilot signals containing the CSI of all the users, in downlink communication, the distributed users merely receive the pilot signals containing their own CSI and cannot leverage the correlation in different users' channels revealed in [1].

Quantization

MUSIC Algorithm for IRS-Assisted AOA Estimation

no code implementations6 Sep 2023 QiPeng Wang, Liang Liu, Shuowen Zhang

In this paper, we consider a more challenging AOA estimation setup in the intelligent reflecting surface (IRS) assisted integrated sensing and communication (ISAC) system, where LOS paths do not exist between the BS and the users, while the users' signals can be transmitted to the BS merely via their LOS paths to the IRS as well as the LOS path from the IRS to the BS.

6G Radio Testbeds: Requirements, Trends, and Approaches

no code implementations13 Sep 2023 Gilles Callebaut, Liang Liu, Thomas Eriksson, Liesbet Van der Perre, Ove Edfors, Christian Fager

The proof of the pudding is in the eating - that is why 6G testbeds are essential in the progress towards the next generation of wireless networks.

Detecting Abrupt Change of Channel Covariance Matrix in IRS-Assisted Communication

no code implementations26 Oct 2023 Runnan Liu, Liang Liu, Yin Xu, Dazhi He, Wenjun Zhang, Chang Wen Chen

We first categorize two types of channel covariance matrix changes based on their impact on system design: Type I change, which denotes the change in the BS receive covariance matrix, and Type II change, which denotes the change in the IRS transmit/receive covariance matrix.

User-Assisted Networked Sensing in OFDM Cellular Network with Erroneous Anchor Position Information

no code implementations20 Dec 2023 Xianzhen Guo, Qin Shi, Liang Liu, Shuowen Zhang

However, in practice, the number of BSs possessing LOS paths to a target can be small, leading to marginal networked sensing gain.

Outlier Detection Position

Fact-checking based fake news detection: a review

no code implementations3 Jan 2024 Yuzhou Yang, Yangming Zhou, Qichao Ying, Zhenxing Qian, Dan Zeng, Liang Liu

This paper reviews and summarizes the research results on fact-based fake news from the perspectives of tasks and problems, algorithm strategies, and datasets.

Fact Checking Fake News Detection

Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection

no code implementations6 Jan 2024 Yuanpeng Tu, Boshen Zhang, Liang Liu, Yuxi Li, Xuhai Chen, Jiangning Zhang, Yabiao Wang, Chengjie Wang, Cai Rong Zhao

Industrial anomaly detection is generally addressed as an unsupervised task that aims at locating defects with only normal training samples.

Anomaly Detection

Multi-target Detection for Reconfigurable Holographic Surfaces Enabled Radar

no code implementations17 Jan 2024 XiaoYu Zhang, Haobo Zhang, Ruoqi Deng, Liang Liu, Boya Di

Multi-target detection is one of the primary tasks in radar-based localization and sensing, typically built on phased array antennas.

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views

no code implementations7 Feb 2024 Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao

By combining two complementing models, LEVI effectively suppresses problematic features in both the fine-tuning data and pre-trained model and preserves useful features for new tasks.

Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model

no code implementations21 Feb 2024 Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao

Further, to accommodate the dissimilarity among the teachers in the committee, we introduce DiverseDistill, which allows the student to understand the expertise of each teacher and extract task knowledge.

Knowledge Distillation Transfer Learning

Dual-path Frequency Discriminators for Few-shot Anomaly Detection

no code implementations7 Mar 2024 Yuhu Bai, Jiangning Zhang, Yuhang Dong, Guanzhong Tian, Liang Liu, Yunkang Cao, Yabiao Wang, Chengjie Wang

We consider anomaly detection as a discriminative classification problem, wherefore the dual-path feature discrimination module is employed to detect and locate the image-level and feature-level anomalies in the feature space.

Anomaly Detection

Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection

no code implementations18 Mar 2024 Liren He, Zhengkai Jiang, Jinlong Peng, Liang Liu, Qiangang Du, Xiaobin Hu, Wenbing Zhu, Mingmin Chi, Yabiao Wang, Chengjie Wang

In the field of multi-class anomaly detection, reconstruction-based methods derived from single-class anomaly detection face the well-known challenge of ``learning shortcuts'', wherein the model fails to learn the patterns of normal samples as it should, opting instead for shortcuts such as identity mapping or artificial noise elimination.

Anomaly Detection

Leveraging A Variety of Anchors in Cellular Network for Ubiquitous Sensing

no code implementations26 Mar 2024 Liang Liu, Shuowen Zhang, Shuguang Cui

A key challenge of 6G-oriented ISAC lies in how to perform ubiquitous sensing based on the communication signals and devices.

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