Search Results for author:
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)
“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。”
Networked Sensing in 6G Cellular Networks: Opportunities and Challenges
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
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
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
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
Simulation results show that the proposed SDOAnet outperforms the existing DOA estimation methods with the effect of the imperfect array.
STC: Spatio-Temporal Contrastive Learning for Video Instance Segmentation
Video Instance Segmentation (VIS) is a task that simultaneously requires classification, segmentation, and instance association in a video.
Ranked #4 on
Video Instance Segmentation
on OVIS validation
Exploiting Temporal Side Information in Massive IoT Connectivity
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.
ISDNet: Integrating Shallow and Deep Networks for Efficient Ultra-High Resolution Segmentation
The huge burden of computation and memory are two obstacles in ultra-high resolution image segmentation.
Multilayer Graph Contrastive Clustering Network
To this end, we propose a generic and effective autoencoder framework for multilayer graph clustering named Multilayer Graph Contrastive Clustering Network (MGCCN).
SelFSR: Self-Conditioned Face Super-Resolution in the Wild via Flow Field Degradation Network
To tackle this problem, we propose a novel domain-adaptive degradation network for face super-resolution in the wild.
Detection of Abrupt Change in Channel Covariance Matrix for Multi-Antenna Communication
This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.
LuMaMi28: Real-Time Millimeter-Wave Massive MIMO Systems with Antenna Selection
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
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
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
Unreliable labels derived from large-scale dataset prevent neural networks from fully exploring the data.
Smoothed Multi-View Subspace Clustering
In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views.
On Massive IoT Connectivity with Temporally-Correlated User Activity
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
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).
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation
To obtainmore accurate depth estimation in large gradient regions, itis necessary to obtain high-resolution features with spatialand semantic information.
Distributed and Scalable Uplink Processing for LIS: Algorithm, Architecture, and Design Trade-offs
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
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
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
A great amount of endeavour has recently been devoted to the joint device activity detection and channel estimation problem in massive machine-type communications.
DTVNet: Dynamic Time-lapse Video Generation via Single Still Image
The proposed DTVNet consists of two submodules: \emph{Optical Flow Encoder} (OFE) and \emph{Dynamic Video Generator} (DVG).
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning
Inspired by scale weighing, we propose a novel 'counting scale' termed LibraNet where the count value is analogized by weight.
A New Accelerated Stochastic Gradient Method with Momentum
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
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.
APB2Face: Audio-guided face reenactment with auxiliary pose and blink signals
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.
A Learning Framework for n-bit Quantized Neural Networks toward FPGAs
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.
Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation
Unsupervised learning of optical flow, which leverages the supervision from view synthesis, has emerged as a promising alternative to supervised methods.
Ranked #1 on
Optical Flow Estimation
on KITTI 2015 unsupervised
(Fl-all metric)
Extended Feature Pyramid Network for Small Object Detection
Small object detection remains an unsolved challenge because it is hard to extract information of small objects with only a few pixels.
Processing Distribution and Architecture Tradeoff for Large Intelligent Surface Implementation
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
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.
From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
A dense region can always be divided until sub-region counts are within the previously observed closed set.
Ranked #6 on
Crowd Counting
on ShanghaiTech B
PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning
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.
FReeNet: Multi-Identity Face Reenactment
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.
An efficient deep learning hashing neural network for mobile visual search
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
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.
