Search Results for author: Fei Jiang

Found 27 papers, 17 papers with code

Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

1 code implementation10 May 2023 Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan

We design a dual-intent network to learn user intent from an attention mechanism and the distribution of historical data respectively, which can simulate users' decision-making process in interacting with a new item.

Decision Making Session-Based Recommendations +1

BPJDet: Extended Object Representation for Generic Body-Part Joint Detection

1 code implementation21 Apr 2023 Huayi Zhou, Fei Jiang, Jiaxin Si, Yue Ding, Hongtao Lu

In this paper, we focus on the joint detection of human body and its corresponding parts.

Head Detection

DirectMHP: Direct 2D Multi-Person Head Pose Estimation with Full-range Angles

1 code implementation2 Feb 2023 Huayi Zhou, Fei Jiang, Hongtao Lu

We present comprehensive comparisons with state-of-the-art single HPE methods on public benchmarks, as well as superior baseline results on our constructed MPHPE datasets.

Head Detection Head Pose Estimation

Body-Part Joint Detection and Association via Extended Object Representation

1 code implementation15 Dec 2022 Huayi Zhou, Fei Jiang, Hongtao Lu

This paper focuses on the problem of joint detection of human body and its corresponding parts.

An Intuitive and Unconstrained 2D Cube Representation for Simultaneous Head Detection and Pose Estimation

no code implementations7 Dec 2022 Huayi Zhou, Fei Jiang, Lili Xiong, Hongtao Lu

Most recent head pose estimation (HPE) methods are dominated by the Euler angle representation.

Ranked #8 on Head Pose Estimation on BIWI (MAE (trained with BIWI data) metric)

Head Detection Head Pose Estimation

StuArt: Individualized Classroom Observation of Students with Automatic Behavior Recognition and Tracking

1 code implementation6 Nov 2022 Huayi Zhou, Fei Jiang, Jiaxin Si, Lili Xiong, Hongtao Lu

In this paper, we present StuArt, a novel automatic system designed for the individualized classroom observation, which empowers instructors to concern the learning status of each student.

SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection

1 code implementation4 Nov 2022 Huayi Zhou, Fei Jiang, Hongtao Lu

Domain adaptive object detection (DAOD) aims to alleviate transfer performance degradation caused by the cross-domain discrepancy.

Domain Adaptation Knowledge Distillation +3

Joint Multi-Person Body Detection and Orientation Estimation via One Unified Embedding

1 code implementation27 Oct 2022 Huayi Zhou, Fei Jiang, Jiaxin Si, Hongtao Lu

In the paper, we propose a single-stage end-to-end trainable framework for tackling the HBOE problem with multi-persons.

Autonomous Driving Body Detection +1

Low-Complexity Acoustic Echo Cancellation with Neural Kalman Filtering

1 code implementation23 Jul 2022 Dong Yang, Fei Jiang, Wei Wu, Xuefei Fang, Muyong Cao

The Kalman filter has been adopted in acoustic echo cancellation due to its robustness to double-talk, fast convergence, and good steady-state performance.

Acoustic echo cancellation

CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning

1 code implementation30 May 2022 Di Jin, Luzhi Wang, Yizhen Zheng, Xiang Li, Fei Jiang, Wei Lin, Shirui Pan

As most of the existing graph neural networks yield effective graph representations of a single graph, little effort has been made for jointly learning two graph representations and calculating their similarity score.

Collaborative Filtering Graph Classification +4

Music Source Separation with Generative Flow

1 code implementation19 Apr 2022 Ge Zhu, Jordan Darefsky, Fei Jiang, Anton Selitskiy, Zhiyao Duan

Fully-supervised models for source separation are trained on parallel mixture-source data and are currently state-of-the-art.

Music Source Separation

Student Dangerous Behavior Detection in School

1 code implementation19 Feb 2022 Huayi Zhou, Fei Jiang, Hongtao Lu

Video surveillance systems have been installed to ensure the student safety in schools.

Action Recognition object-detection +1

High-fidelity acoustic signal enhancement for phase-OTDR using supervised learning

no code implementations Optics Express 2021 Fei Jiang, 1 ZHENHAI ZHANG, 1, 5 ZIXIAO LU, 2 HONGLANG LI, 2, 6 YAHUI TIAN, 3 YIXIN ZHANG, 4 AND XUPING ZHANG4

The results show that, the proposed method can well suppress the noise and signal distortion caused by the laser frequency drift, laser phase noise, and interference fading, while recover the acoustic signals with high fidelity.

An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems

3 code implementations3 Apr 2021 You Zhang, Ge Zhu, Fei Jiang, Zhiyao Duan

Spoofing countermeasure (CM) systems are critical in speaker verification; they aim to discern spoofing attacks from bona fide speech trials.

Data Augmentation Multi-Task Learning +2

Deoscillated Graph Collaborative Filtering

1 code implementation4 Nov 2020 Zhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang, Philip S. Yu

Stacking multiple cross-hop propagation layers and locality layers constitutes the DGCF model, which models high-order CF signals adaptively to the locality of nodes and layers.

Collaborative Filtering Recommendation Systems

One-class learning towards generalized voice spoofing detection

3 code implementations27 Oct 2020 You Zhang, Fei Jiang, Zhiyao Duan

Human voices can be used to authenticate the identity of the speaker, but the automatic speaker verification (ASV) systems are vulnerable to voice spoofing attacks, such as impersonation, replay, text-to-speech, and voice conversion.

Speaker Verification Voice Anti-spoofing +1

Y-Vector: Multiscale Waveform Encoder for Speaker Embedding

1 code implementation24 Oct 2020 Ge Zhu, Fei Jiang, Zhiyao Duan

State-of-the-art text-independent speaker verification systems typically use cepstral features or filter bank energies as speech features.

Text-Independent Speaker Verification

Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks

no code implementations8 Nov 2019 Jiahao Liu, Guixiang Ma, Fei Jiang, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin

Specifically, we use graph convolutions to learn the structural and functional joint embedding, where the graph structure is defined with structural connectivity and node features are from the functional connectivity.


Bayesian Model Selection Approach to Boundary Detection with Non-Local Priors

no code implementations NeurIPS 2018 Fei Jiang, Guosheng Yin, Francesca Dominici

Based on non-local prior distributions, we propose a Bayesian model selection (BMS) procedure for boundary detection in a sequence of data with multiple systematic mean changes.

Boundary Detection Change Point Detection +1

Spectral Collaborative Filtering

1 code implementation30 Aug 2018 Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu

Benefiting from the rich information of connectivity existing in the \textit{spectral domain}, SpectralCF is capable of discovering deep connections between users and items and therefore, alleviates the \textit{cold-start} problem for CF.

Collaborative Filtering Recommendation Systems

Bayesian Outdoor Defect Detection

no code implementations30 Aug 2018 Fei Jiang, Guosheng Yin

We implement the Bayesian detector in the motion blurred drone images, in which the detector successfully identifies the hail damages on the rough surface and substantially enhances the accuracy of the entire defect detection pipeline.

Defect Detection

Efficient Two-Dimensional Sparse Coding Using Tensor-Linear Combination

no code implementations28 Mar 2017 Fei Jiang, Xiao-Yang Liu, Hongtao Lu, Ruimin Shen

Sparse coding (SC) is an automatic feature extraction and selection technique that is widely used in unsupervised learning.

Denoising Vocal Bursts Valence Prediction

Graph Regularized Tensor Sparse Coding for Image Representation

no code implementations27 Mar 2017 Fei Jiang, Xiao-Yang Liu, Hongtao Lu, Ruimin Shen

Sparse coding (SC) is an unsupervised learning scheme that has received an increasing amount of interests in recent years.

Clustering Image Clustering

Manifold regularization in structured output space for semi-supervised structured output prediction

no code implementations12 Aug 2015 Fei Jiang, Lili Jia, Xiaobao Sheng, Riley LeMieux

Structured output prediction aims to learn a predictor to predict a structured output from a input data vector.

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