Search Results for author: Feng Zhou

Found 76 papers, 24 papers with code

Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures

no code implementations5 Feb 2024 Zenan Ling, Longbo Li, Zhanbo Feng, Yixuan Zhang, Feng Zhou, Robert C. Qiu, Zhenyu Liao

Deep equilibrium models (DEQs), as a typical implicit neural network, have demonstrated remarkable success on various tasks.

Mitigating Label Bias in Machine Learning: Fairness through Confident Learning

no code implementations14 Dec 2023 Yixuan Zhang, Boyu Li, Zenan Ling, Feng Zhou

In this paper, we demonstrate that despite only having access to the biased labels, it is possible to eliminate bias by filtering the fairest instances within the framework of confident learning.


Concept-centric Personalization with Large-scale Diffusion Priors

1 code implementation13 Dec 2023 Pu Cao, Lu Yang, Feng Zhou, Tianrui Huang, Qing Song

In this work, we present the task of customizing large-scale diffusion priors for specific concepts as concept-centric personalization.

Diffusion Personalization

A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check

1 code implementation13 Oct 2023 Haojing Huang, Jingheng Ye, Qingyu Zhou, Yinghui Li, Yangning Li, Feng Zhou, Hai-Tao Zheng

In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task in an end-to-end fashion.

Zero-shot Inversion Process for Image Attribute Editing with Diffusion Models

no code implementations30 Aug 2023 Zhanbo Feng, Zenan Ling, Ci Gong, Feng Zhou, Jie Li, Robert C. Qiu

Existing works tend to use either image-guided methods, which provide a visual reference but lack control over semantic coherence, or text-guided methods, which ensure faithfulness to text guidance but lack visual quality.

Attribute Denoising

Heterogeneous Multi-Task Gaussian Cox Processes

1 code implementation29 Aug 2023 Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu

This paper presents a novel extension of multi-task Gaussian Cox processes for modeling multiple heterogeneous correlated tasks jointly, e. g., classification and regression, via multi-output Gaussian processes (MOGP).

Bayesian Inference Data Augmentation +2

Enhancing Phrase Representation by Information Bottleneck Guided Text Diffusion Process for Keyphrase Extraction

no code implementations17 Aug 2023 Yuanzhen Luo, Qingyu Zhou, Feng Zhou

Keyphrase extraction (KPE) is an important task in Natural Language Processing for many scenarios, which aims to extract keyphrases that are present in a given document.

Keyphrase Extraction

On the (In)Effectiveness of Large Language Models for Chinese Text Correction

no code implementations18 Jul 2023 Yinghui Li, Haojing Huang, Shirong Ma, Yong Jiang, Yangning Li, Feng Zhou, Hai-Tao Zheng, Qingyu Zhou

Recently, the development and progress of Large Language Models (LLMs) have amazed the entire Artificial Intelligence community.

Grammatical Error Correction

RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network

1 code implementation4 Jul 2023 Feng Zhou, Antonio Cicone, Haomin Zhou

Inspired by the successful applications of deep learning in fields like image processing and natural language processing, and given the lack in the literature of works in which deep learning techniques are used directly to decompose non-stationary signals into simple oscillatory components, we use the convolutional neural network, residual structure and nonlinear activation function to compute in an innovative way the local average of the signal, and study a new non-stationary signal decomposition method under the framework of deep learning.

An Improved Baseline Framework for Pose Estimation Challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop

no code implementations13 Mar 2023 Jiajun Fu, Yonghao Dang, Ruoqi Yin, Shaojie Zhang, Feng Zhou, Wending Zhao, Jianqin Yin

This technical report describes our first-place solution to the pose estimation challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop.

Human Detection Pose Estimation

Improving Crowded Object Detection via Copy-Paste

no code implementations22 Nov 2022 Jiangfan Deng, Dewen Fan, Xiaosong Qiu, Feng Zhou

Crowdedness caused by overlapping among similar objects is a ubiquitous challenge in the field of 2D visual object detection.

Data Augmentation Object +2

Accelerated Linearized Laplace Approximation for Bayesian Deep Learning

1 code implementation23 Oct 2022 Zhijie Deng, Feng Zhou, Jun Zhu

Laplace approximation (LA) and its linearized variant (LLA) enable effortless adaptation of pretrained deep neural networks to Bayesian neural networks.

De-biased Representation Learning for Fairness with Unreliable Labels

no code implementations1 Aug 2022 Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

In other words, the fair pre-processing methods ignore the discrimination encoded in the labels either during the learning procedure or the evaluation stage.

Fairness Representation Learning

Towards Privacy-Preserving, Real-Time and Lossless Feature Matching

1 code implementation30 Jul 2022 Qiang Meng, Feng Zhou

Given limited public projects in this field, codes of our method and implemented baselines are made open-source in https://github. com/IrvingMeng/SecureVector.

Face Recognition Image Retrieval +3

Fully-integrated multipurpose microwave frequency identification system on a single chip

no code implementations17 Feb 2022 Yuhan Yao, Yuhe Zhao, Yanxian Wei, Feng Zhou, Daigao Chen, Yuguang Zhang, Xi Xiao, Ming Li, Jianji Dong, Shaohua Yu, Xinliang Zhang

We demonstrate a fully-integrated multipurpose microwave frequency identification system on silicon-on-insulator platform.

Basket-based Softmax

no code implementations23 Jan 2022 Qiang Meng, Xinqian Gu, Xiaqing Xu, Feng Zhou

Experimentally, we demonstrate the efficiency and superiority of the BBS on the tasks of face recognition and re-identification, with both simulated and real-world datasets.

Face Recognition

Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer

no code implementations12 Dec 2021 Shiye Lei, Zhuozhuo Tu, Leszek Rutkowski, Feng Zhou, Li Shen, Fengxiang He, DaCheng Tao

Bayesian neural networks (BNNs) have become a principal approach to alleviate overconfident predictions in deep learning, but they often suffer from scaling issues due to a large number of distribution parameters.

Adversarial Robustness Uncertainty Quantification +1

Continuous-time edge modelling using non-parametric point processes

no code implementations NeurIPS 2021 Xuhui Fan, Bin Li, Feng Zhou, Scott Sisson

The mutually-exciting Hawkes process (ME-HP) is a natural choice to model reciprocity, which is an important attribute of continuous-time edge (dyadic) data.

Attribute Gaussian Processes +2

Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline

no code implementations5 Nov 2021 Yangtao Zhang, X. Jessie Yang, Feng Zhou

The advancement in machine learning and artificial intelligence is promoting the testing and deployment of autonomous vehicles (AVs) on public roads.

Autonomous Driving Transfer Learning

Additive Poisson Process: Learning Intensity of Higher-Order Interaction in Poisson Processes

no code implementations29 Sep 2021 Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama

We present the Additive Poisson Process (APP), a novel framework that can model the higher-order interaction effects of the intensity functions in Poisson processes using projections into lower-dimensional space.

Additive models

Deep Ensemble as a Gaussian Process Posterior

no code implementations29 Sep 2021 Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu

Deep Ensemble (DE) is a flexible, feasible, and effective alternative to Bayesian neural networks (BNNs) for uncertainty estimation in deep learning.

Variational Inference

Learning Compatible Embeddings

1 code implementation ICCV 2021 Qiang Meng, Chixiang Zhang, Xiaoqiang Xu, Feng Zhou

Achieving backward compatibility when rolling out new models can highly reduce costs or even bypass feature re-encoding of existing gallery images for in-production visual retrieval systems.

Knowledge Distillation Retrieval

PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition

no code implementations25 Jul 2021 Qiang Meng, Xiaqing Xu, Xiaobo Wang, Yang Qian, Yunxiao Qin, Zezheng Wang, Chenxu Zhao, Feng Zhou, Zhen Lei

Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e. g., in cases of surveillance and photo-tagging).

Face Recognition

Predicting Driver Takeover Time in Conditionally Automated Driving

no code implementations20 Jul 2021 Jackie Ayoub, Na Du, X. Jessie Yang, Feng Zhou

Their main effects and interaction effects on takeover time were examined.

Bias-Tolerant Fair Classification

no code implementations7 Jul 2021 Yixuan Zhang, Feng Zhou, Zhidong Li, Yang Wang, Fang Chen

Therefore, we propose a Bias-TolerantFAirRegularizedLoss (B-FARL), which tries to regain the benefits using data affected by label bias and selection bias.

Classification Fairness +2

Nonlinear Hawkes Processes in Time-Varying System

no code implementations9 Jun 2021 Feng Zhou, Quyu Kong, Yixuan Zhang, Cheng Feng, Jun Zhu

Hawkes processes are a class of point processes that have the ability to model the self- and mutual-exciting phenomena.

Bayesian Inference Point Processes +1

Robust Lightweight Facial Expression Recognition Network with Label Distribution Training

1 code implementation AAAI Conference on Artificial Intelligence 2021 Zengqun Zhao, Qingshan Liu, Feng Zhou

This paper presents an efficiently robust facial expression recognition (FER) network, named EfficientFace, which holds much fewer parameters but more robust to the FER in the wild.

Ranked #11 on Facial Expression Recognition (FER) on RAF-DB (Overall Accuracy metric)

Facial Expression Recognition (FER)

Unsupervised Classification for Polarimetric SAR Data Using Variational Bayesian Wishart Mixture Model with Inverse Gamma-Gamma Prior

no code implementations4 Apr 2021 Shijie Ren, Feng Zhou, Changlong Wang

Although various clustering methods have been successfully applied to polarimetric synthetic aperture radar (PolSAR) image clustering tasks, most of the available approaches fail to realize automatic determination of cluster number, nor have they derived an exact distribution for the number of looks.

Clustering Image Clustering

MagFace: A Universal Representation for Face Recognition and Quality Assessment

2 code implementations CVPR 2021 Qiang Meng, Shichao Zhao, Zhida Huang, Feng Zhou

This paper proposes MagFace, a category of losses that learn a universal feature embedding whose magnitude can measure the quality of the given face.

 Ranked #1 on Face Verification on IJB-C (training dataset metric)

Clustering Face Quality Assessement +1

Combat COVID-19 Infodemic Using Explainable Natural Language Processing Models

no code implementations1 Mar 2021 Jackie Ayoub, X. Jessie Yang, Feng Zhou

By augmenting the data using back-translation, we doubled the sample size of the dataset and the DistilBERT model was able to obtain good performance (accuracy: 0. 972; areas under the curve: 0. 993) in detecting misinformation about COVID-19.

Fact Checking Fake News Detection +1

Coexistience of phononic six-fold, four-fold and three-fold excitations in ternary antimonide Zr3Ni3Sb4

no code implementations22 Feb 2021 Mingmin Zhong, Ying Liu, Feng Zhou, Minquan Kuang, Tie Yang, Xiaotian Wang, Gang Zhang

However, these materials are uncommon because these excitations in electronic systems are usually broken by spin-orbit coupling (SOC) and normally far from the Fermi level.

Materials Science

Searching for Alignment in Face Recognition

no code implementations10 Feb 2021 Xiaqing Xu, Qiang Meng, Yunxiao Qin, Jianzhu Guo, Chenxu Zhao, Feng Zhou, Zhen Lei

A standard pipeline of current face recognition frameworks consists of four individual steps: locating a face with a rough bounding box and several fiducial landmarks, aligning the face image using a pre-defined template, extracting representations and comparing.

Face Alignment Face Detection +2

Body-Face Joint Detection via Embedding and Head Hook

1 code implementation ICCV 2021 Junfeng Wan, Jiangfan Deng, Xiaosong Qiu, Feng Zhou

Detecting pedestrians and their associated faces jointly is a challenging task. On one hand, body or face could be absent because of occlusion or non-frontal human pose. On the other hand, the association becomes difficult or even miss-leading in crowded scenes due to the lack of strong correlational evidence.

Pedestrian Detection

Learning Joint Intensity in a Multivariate Poisson Process on Statistical Manifolds

no code implementations NeurIPS Workshop DL-IG 2020 Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama

Learning of the model is achieved via convex optimization, thanks to the dually flat statistical manifold generated by the log-linear model.

Additive models

Matching Guided Distillation

1 code implementation ECCV 2020 Kaiyu Yue, Jiangfan Deng, Feng Zhou

However, this introduces two problems: a) The adaptation module brings more parameters into training.

Visible Feature Guidance for Crowd Pedestrian Detection

no code implementations23 Aug 2020 Zhida Huang, Kaiyu Yue, Jiangfan Deng, Feng Zhou

Then we perform NMS only on visible bounding boxes to achieve the best fitting full box in inference.

Pedestrian Detection

Do not forget interaction: Predicting fatality of COVID-19 patients using logistic regression

no code implementations30 Jun 2020 Feng Zhou, Tao Chen, Baiying Lei

Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks can be recovered or not depends, to a large extent, on how early they will be treated appropriately before irreversible consequences are caused to the patients by the virus.


Efficient Inference of Flexible Interaction in Spiking-neuron Networks

no code implementations ICLR 2021 Feng Zhou, Yixuan Zhang, Jun Zhu

Hawkes process provides an effective statistical framework for analyzing the time-dependent interaction of neuronal spiking activities.

Additive Poisson Process: Learning Intensity of Higher-Order Interaction in Stochastic Processes

no code implementations16 Jun 2020 Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama

We present the Additive Poisson Process (APP), a novel framework that can model the higher-order interaction effects of the intensity functions in stochastic processes using lower dimensional projections.

Additive models

Searching Central Difference Convolutional Networks for Face Anti-Spoofing

4 code implementations CVPR 2020 Zitong Yu, Chenxu Zhao, Zezheng Wang, Yunxiao Qin, Zhuo Su, Xiaobai Li, Feng Zhou, Guoying Zhao

Here we propose a novel frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information.

Face Anti-Spoofing Face Recognition +1

Deep Variational Luenberger-type Observer for Stochastic Video Prediction

no code implementations12 Feb 2020 Dong Wang, Feng Zhou, Zheng Yan, Guang Yao, Zongxuan Liu, Wennan Ma, Cewu Lu

Our model builds upon an variational encoder which transforms the input video into a latent feature space and a Luenberger-type observer which captures the dynamic evolution of the latent features.

Representation Learning Video Prediction +1

Examining the Effects of Emotional Valence and Arousal on Takeover Performance in Conditionally Automated Driving

no code implementations13 Jan 2020 Na Du, Feng Zhou, Elizabeth Pulver, Dawn M. Tilbury, Lionel P. Robert, Anuj K. Pradhan, X. Jessie Yang

Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed.

Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation

no code implementations29 Oct 2019 Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

In this paper, we consider the sigmoid Gaussian Hawkes process model: the baseline intensity and triggering kernel of Hawkes process are both modeled as the sigmoid transformation of random trajectories drawn from Gaussian processes (GP).

Bayesian Inference Gaussian Processes +1

Recognizing Part Attributes with Insufficient Data

1 code implementation ICCV 2019 Xiangyun Zhao, Yi Yang, Feng Zhou, Xiao Tan, Yuchen Yuan, Yingze Bao, Ying Wu

Although great progress has been made to apply object-level recognition, recognizing the attributes of parts remains less applicable since the training data for part attributes recognition is usually scarce especially for internet-scale applications.


Efficient EM-Variational Inference for Hawkes Process

no code implementations29 May 2019 Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen

In classical Hawkes process, the baseline intensity and triggering kernel are assumed to be a constant and parametric function respectively, which limits the model flexibility.

Variational Inference

Compact Generalized Non-local Network

2 code implementations NeurIPS 2018 Kaiyu Yue, Ming Sun, Yuchen Yuan, Feng Zhou, Errui Ding, Fuxin Xu

The non-local module is designed for capturing long-range spatio-temporal dependencies in images and videos.

Object Detection Object Recognition +1

Fine-grained Video Categorization with Redundancy Reduction Attention

no code implementations ECCV 2018 Chen Zhu, Xiao Tan, Feng Zhou, Xiao Liu, Kaiyu Yue, Errui Ding, Yi Ma

Specifically, it firstly summarizes the video by weight-summing all feature vectors in the feature maps of selected frames with a spatio-temporal soft attention, and then predicts which channels to suppress or to enhance according to this summary with a learned non-linear transform.

Action Recognition Video Classification

Improving Annotation for 3D Pose Dataset of Fine-Grained Object Categories

2 code implementations19 Oct 2018 Yaming Wang, Xiao Tan, Yi Yang, Ziyu Li, Xiao Liu, Feng Zhou, Larry S. Davis

Existing 3D pose datasets of object categories are limited to generic object types and lack of fine-grained information.

3D Pose Estimation Object +1

Hyperspectral image classification using spectral-spatial LSTMs

no code implementations20 Aug 2018 Feng Zhou, Renlong Hang, Qingshan Liu, Xiaotong Yuan

Specifically, for each pixel, we feed its spectral values in different channels into Spectral LSTM one by one to learn the spectral feature.

Classification General Classification +1

Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

1 code implementation ECCV 2018 Ming Sun, Yuchen Yuan, Feng Zhou, Errui Ding

Attention-based learning for fine-grained image recognition remains a challenging task, where most of the existing methods treat each object part in isolation, while neglecting the correlations among them.

Fine-Grained Image Recognition Metric Learning

Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model

no code implementations2 May 2018 Feng Zhou, Shu Kong, Charless Fowlkes, Tao Chen, Baiying Lei

Specifically, we first mapped facial expressions into dimensional measures so that we transformed facial expression analysis from a classification problem to a regression one.

General Classification regression

Deep Metric Learning with Angular Loss

1 code implementation ICCV 2017 Jian Wang, Feng Zhou, Shilei Wen, Xiao Liu, Yuanqing Lin

The modern image search system requires semantic understanding of image, and a key yet under-addressed problem is to learn a good metric for measuring the similarity between images.

Image Retrieval Metric Learning

Kernel Pooling for Convolutional Neural Networks

no code implementations CVPR 2017 Yin Cui, Feng Zhou, Jiang Wang, Xiao Liu, Yuanqing Lin, Serge Belongie

We demonstrate how to approximate kernels such as Gaussian RBF up to a given order using compact explicit feature maps in a parameter-free manner.

Face Recognition Fine-Grained Visual Categorization +2

Hyperspectral Image Classification with Markov Random Fields and a Convolutional Neural Network

1 code implementation1 May 2017 Xiangyong Cao, Feng Zhou, Lin Xu, Deyu Meng, Zongben Xu, John Paisley

This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian framework.

Ranked #13 on Hyperspectral Image Classification on Indian Pines (Overall Accuracy metric, using extra training data)

Classification General Classification +1

Dynamic Computational Time for Visual Attention

1 code implementation30 Mar 2017 Zhichao Li, Yi Yang, Xiao Liu, Feng Zhou, Shilei Wen, Wei Xu

We propose a dynamic computational time model to accelerate the average processing time for recurrent visual attention (RAM).

reinforcement-learning Reinforcement Learning (RL)

Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

1 code implementation23 Mar 2017 Qingshan Liu, Feng Zhou, Renlong Hang, Xiao-Tong Yuan

In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to address it.

General Classification Hyperspectral Image Classification

Deep Deformation Network for Object Landmark Localization

no code implementations3 May 2016 Xiang Yu, Feng Zhou, Manmohan Chandraker

We propose a novel cascaded framework, namely deep deformation network (DDN), for localizing landmarks in non-rigid objects.

Face Alignment Object +1

Fully Convolutional Attention Networks for Fine-Grained Recognition

no code implementations22 Mar 2016 Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou, Yuanqing Lin

Fine-grained recognition is challenging due to its subtle local inter-class differences versus large intra-class variations such as poses.

reinforcement-learning Reinforcement Learning (RL)

Embedding Label Structures for Fine-Grained Feature Representation

no code implementations CVPR 2016 Xiaofan Zhang, Feng Zhou, Yuanqing Lin, Shaoting Zhang

However, previous studies have rarely focused on learning a fined-grained and structured feature representation that is able to locate similar images at different levels of relevance, e. g., discovering cars from the same make or the same model, both of which require high precision.

Fine-Grained Image Classification General Classification +3

Fine-grained Image Classification by Exploring Bipartite-Graph Labels

no code implementations CVPR 2016 Feng Zhou, Yuanqing Lin

To facilitate the study, we construct a new food benchmark dataset, which consists of 37, 885 food images collected from 6 restaurants and totally 975 menus.

Classification Fine-Grained Image Classification +4

Time-Mapping Using Space-Time Saliency

no code implementations CVPR 2014 Feng Zhou, Sing Bing Kang, Michael F. Cohen

We describe a new approach for generating regular-speed, low-frame-rate (LFR) video from a high-frame-rate (HFR) input while preserving the important moments in the original.

Ranked #6 on Video Salient Object Detection on DAVSOD-Difficult20 (using extra training data)

Tone Mapping Video Salient Object Detection

Deformable Graph Matching

no code implementations CVPR 2013 Feng Zhou, Fernando de la Torre

This paper proposes deformable graph matching (DGM), an extension of GM for matching graphs subject to global rigid and non-rigid geometric constraints.

Graph Matching

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