Search Results for author: Xiaopeng Hong

Found 36 papers, 9 papers with code

Topology-Preserving Class-Incremental Learning

no code implementations ECCV 2020 Xiaoyu Tao, Xinyuan Chang, Xiaopeng Hong, Xing Wei, Yihong Gong

A well-known issue for class-incremental learning is the catastrophic forgetting phenomenon, where the network's recognition performance on old classes degrades severely when incrementally learning new classes.

class-incremental learning Incremental Learning

S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning

1 code implementation26 Jul 2022 Yabin Wang, Zhiwu Huang, Xiaopeng Hong

In this paper, we propose one simple paradigm (named as S-Prompting) and two concrete approaches to highly reduce the forgetting degree in one of the most typical continual learning scenarios, i. e., domain increment learning (DIL).

Continual Learning Incremental Learning

Deep Class Incremental Learning from Decentralized Data

no code implementations11 Mar 2022 Xiaohan Zhang, Songlin Dong, Jinjie Chen, Qi Tian, Yihong Gong, Xiaopeng Hong

In this paper, we focus on a new and challenging decentralized machine learning paradigm in which there are continuous inflows of data to be addressed and the data are stored in multiple repositories.

class-incremental learning Incremental Learning +1

Boosting Crowd Counting via Multifaceted Attention

1 code implementation CVPR 2022 Hui Lin, Zhiheng Ma, Rongrong Ji, YaoWei Wang, Xiaopeng Hong

Secondly, we design the Local Attention Regularization to supervise the training of LRA by minimizing the deviation among the attention for different feature locations.

Crowd Counting

Object Counting: You Only Need to Look at One

no code implementations11 Dec 2021 Hui Lin, Xiaopeng Hong, Yabin Wang

This paper aims to tackle the challenging task of one-shot object counting.

Object Counting

Short and Long Range Relation Based Spatio-Temporal Transformer for Micro-Expression Recognition

no code implementations10 Dec 2021 Liangfei Zhang, Xiaopeng Hong, Ognjen Arandjelovic, Guoying Zhao

Being spontaneous, micro-expressions are useful in the inference of a person's true emotions even if an attempt is made to conceal them.

Micro-Expression Recognition

3D Visual Tracking Framework with Deep Learning for Asteroid Exploration

no code implementations21 Nov 2021 Dong Zhou, Gunaghui Sun, Xiaopeng Hong

3D visual tracking is significant to deep space exploration programs, which can guarantee spacecraft to flexibly approach the target.

Visual Tracking

Anomaly Detection via Self-organizing Map

no code implementations21 Jul 2021 Ning li, Kaitao Jiang, Zhiheng Ma, Xing Wei, Xiaopeng Hong, Yihong Gong

Anomaly detection plays a key role in industrial manufacturing for product quality control.

Unsupervised Anomaly Detection

Direct Measure Matching for Crowd Counting

no code implementations4 Jul 2021 Hui Lin, Xiaopeng Hong, Zhiheng Ma, Xing Wei, Yunfeng Qiu, YaoWei Wang, Yihong Gong

Second, we derive a semi-balanced form of Sinkhorn divergence, based on which a Sinkhorn counting loss is designed for measure matching.

Crowd Counting

Image-to-image Translation via Hierarchical Style Disentanglement

1 code implementation CVPR 2021 Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji

Recently, image-to-image translation has made significant progress in achieving both multi-label (\ie, translation conditioned on different labels) and multi-style (\ie, generation with diverse styles) tasks.

Disentanglement Multimodal Unsupervised Image-To-Image Translation +1

Towards a Universal Model for Cross-Dataset Crowd Counting

no code implementations ICCV 2021 Zhiheng Ma, Xiaopeng Hong, Xing Wei, Yunfeng Qiu, Yihong Gong

This paper proposes to handle the practical problem of learning a universal model for crowd counting across scenes and datasets.

Crowd Counting

Aha! Adaptive History-Driven Attack for Decision-Based Black-Box Models

no code implementations ICCV 2021 Jie Li, Rongrong Ji, Peixian Chen, Baochang Zhang, Xiaopeng Hong, Ruixin Zhang, Shaoxin Li, Jilin Li, Feiyue Huang, Yongjian Wu

A common practice is to start from a large perturbation and then iteratively reduce it with a deterministic direction and a random one while keeping it adversarial.

Dimensionality Reduction

Micro-expression spotting: A new benchmark

no code implementations24 Jul 2020 Thuong-Khanh Tran, Quang-Nhat Vo, Xiaopeng Hong, Xiaobai Li, Guoying Zhao

Micro-expressions (MEs) are brief and involuntary facial expressions that occur when people are trying to hide their true feelings or conceal their emotions.

Micro-Expression Spotting

Few-Shot Class-Incremental Learning

1 code implementation CVPR 2020 Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, Songlin Dong, Xing Wei, Yihong Gong

FSCIL requires CNN models to incrementally learn new classes from very few labelled samples, without forgetting the previously learned ones.

class-incremental learning Incremental Learning +1

Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

1 code implementation11 Nov 2019 Wei Peng, Xiaopeng Hong, Haoyu Chen, Guoying Zhao

Human action recognition from skeleton data, fueled by the Graph Convolutional Network (GCN), has attracted lots of attention, due to its powerful capability of modeling non-Euclidean structure data.

Action Recognition Neural Architecture Search +1

Beyond Universal Person Re-ID Attack

no code implementations30 Oct 2019 Wenjie Ding, Xing Wei, Rongrong Ji, Xiaopeng Hong, Qi Tian, Yihong Gong

We propose a \emph{more universal} adversarial perturbation (MUAP) method for both image-agnostic and model-insensitive person Re-ID attack.

General Classification Person Re-Identification

Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection

1 code implementation ICCV 2019 Yingyue Xu, Dan Xu, Xiaopeng Hong, Wanli Ouyang, Rongrong Ji, Min Xu, Guoying Zhao

We formulate the CRF graphical model that involves message-passing of feature-feature, feature-prediction, and prediction-prediction, from the coarse scale to the finer scale, to update the features and the corresponding predictions.

object-detection RGB Salient Object Detection +1

Bayesian Loss for Crowd Count Estimation with Point Supervision

4 code implementations ICCV 2019 Zhiheng Ma, Xing Wei, Xiaopeng Hong, Yihong Gong

In crowd counting datasets, each person is annotated by a point, which is usually the center of the head.

Crowd Counting

Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement

1 code implementation ICCV 2019 Zitong Yu, Wei Peng, Xiaobai Li, Xiaopeng Hong, Guoying Zhao

The method includes two parts: 1) a Spatio-Temporal Video Enhancement Network (STVEN) for video enhancement, and 2) an rPPG network (rPPGNet) for rPPG signal recovery.

Video Compression Video Enhancement

Video Action Recognition Via Neural Architecture Searching

no code implementations10 Jul 2019 Wei Peng, Xiaopeng Hong, Guoying Zhao

Deep neural networks have achieved great success for video analysis and understanding.

Action Recognition

Attribute Guided Unpaired Image-to-Image Translation with Semi-supervised Learning

1 code implementation29 Apr 2019 Xinyang Li, Jie Hu, Shengchuan Zhang, Xiaopeng Hong, Qixiang Ye, Chenglin Wu, Rongrong Ji

Especially, AGUIT benefits from two-fold: (1) It adopts a novel semi-supervised learning process by translating attributes of labeled data to unlabeled data, and then reconstructing the unlabeled data by a cycle consistency operation.

Disentanglement Image-to-Image Translation +1

DDNet: Cartesian-polar Dual-domain Network for the Joint Optic Disc and Cup Segmentation

no code implementations18 Apr 2019 Qing Liu, Xiaopeng Hong, Wei Ke, Zailiang Chen, Beiji Zou

In this paper, we propose a novel segmentation approach, named Cartesian-polar dual-domain network (DDNet), which for the first time considers the complementary of the Cartesian domain and the polar domain.

Feature Importance

A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework

no code implementations23 Jan 2019 Wei Peng, Xiaopeng Hong, Yingyue Xu, Guoying Zhao

Facial Micro-expression Recognition (MER) distinguishes the underlying emotional states of spontaneous subtle facialexpressions.

Micro-Expression Recognition

Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions

no code implementations15 Jan 2019 Zhaoqiang Xia, Xiaopeng Hong, Xingyu Gao, Xiaoyi Feng, Guoying Zhao

To exploit the merits of deep learning, we propose a novel deep recurrent convolutional networks based micro-expression recognition approach, capturing the spatial-temporal deformations of micro-expression sequence.

Data Augmentation Micro-Expression Recognition

Cross-Database Micro-Expression Recognition: A Benchmark

no code implementations19 Dec 2018 Yuan Zong, Tong Zhang, Wenming Zheng, Xiaopeng Hong, Chuangao Tang, Zhen Cui, Guoying Zhao

Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis.

Domain Adaptation Micro-Expression Recognition

Micro-Expression Spotting: A Benchmark

no code implementations8 Oct 2017 Xiaopeng Hong, Thuong-Khanh Tran, Guoying Zhao

Micro-expressions are rapid and involuntary facial expressions, which indicate the suppressed or concealed emotions.

Micro-Expression Spotting

PCANet-II: When PCANet Meets the Second Order Pooling

no code implementations30 Sep 2017 Lei Tian, Xiaopeng Hong, Guoying Zhao, Chunxiao Fan, Yue Ming, Matti Pietikäinen

Moreover, it is easy to combine other discriminative and robust cues by using the second order pooling.

Saliency Integration: An Arbitrator Model

no code implementations4 Aug 2016 Yingyue Xu, Xiaopeng Hong, Fatih Porikli, Xin Liu, Jie Chen, Guoying Zhao

Previous offline integration methods usually face two challenges: 1. if most of the candidate saliency models misjudge the saliency on an image, the integration result will lean heavily on those inferior candidate models; 2. an unawareness of the ground truth saliency labels brings difficulty in estimating the expertise of each candidate model.

Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Video

no code implementations3 May 2016 Jing Zhou, Xiaopeng Hong, Fei Su, Guoying Zhao

To overcome this problem, we propose a real-time regression framework based on the recurrent convolutional neural network for automatic frame-level pain intensity estimation.

Pain Intensity Regression

Dynamic texture and scene classification by transferring deep image features

no code implementations1 Feb 2015 Xianbiao Qi, Chun-Guang Li, Guoying Zhao, Xiaopeng Hong, Matti Pietikäinen

Moreover we explore two different implementations of the TCoF scheme, i. e., the \textit{spatial} TCoF and the \textit{temporal} TCoF, in which the mean-removed frames and the difference between two adjacent frames are used as the inputs of the ConvNet, respectively.

Classification General Classification +2

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