Search Results for author: Xuequan Lu

Found 40 papers, 5 papers with code

AI-based Carcinoma Detection and Classification Using Histopathological Images: A Systematic Review

no code implementations18 Jan 2022 Swathi Prabhua, Keerthana Prasada, Antonio Robels-Kelly, Xuequan Lu

In this systematic literature review, we present a comprehensive review of the state-of-the-art approaches reported in carcinoma diagnosis using histopathological images.

3D Intracranial Aneurysm Classification and Segmentation via Unsupervised Dual-branch Learning

no code implementations6 Jan 2022 Di Shao, Xuequan Lu, Xiao Liu

While most existing deep learning research focused on medical images in a supervised way, we introduce an unsupervised method for the detection of intracranial aneurysms based on 3D point cloud data.

Unsupervised Pre-training

Towards Uniform Point Distribution in Feature-preserving Point Cloud Filtering

no code implementations5 Jan 2022 Shuaijun Chen, Jinxi Wang, Wei Pan, Shang Gao, Meili Wang, Xuequan Lu

As a popular representation of 3D data, point cloud may contain noise and need to be filtered before use.

Deep Point Cloud Normal Estimation via Triplet Learning

no code implementations20 Oct 2021 Weijia Wang, Xuequan Lu, Dasith de Silva Edirimuni, Xiao Liu, Antonio Robles-Kelly

It consists of two phases: (a) feature encoding which learns representations of local patches, and (b) normal estimation that takes the learned representation as input and regresses the normal vector.

Rethinking Point Cloud Filtering: A Non-Local Position Based Approach

no code implementations14 Oct 2021 Jinxi Wang, Jincen Jiang, Xuequan Lu, Meili Wang

We then map the non-local similar patches into a canonical space and aggregate the non-local information.

Unsupervised Representation Learning for 3D Point Cloud Data

no code implementations13 Oct 2021 Jincen Jiang, Xuequan Lu, Wanli Ouyang, Meili Wang

Though a number of point cloud learning methods have been proposed to handle unordered points, most of them are supervised and require labels for training.

3D Object Classification Classification +2

Domain Adaptive Semantic Segmentation via Regional Contrastive Consistency Regularization

no code implementations11 Oct 2021 Qianyu Zhou, Chuyun Zhuang, Ran Yi, Xuequan Lu, Lizhuang Ma

In this paper, we propose a novel and fully end-to-end trainable approach, called regional contrastive consistency regularization (RCCR) for domain adaptive semantic segmentation.

Semantic Segmentation Synthetic-to-Real Translation +1

A Robust Scheme for 3D Point Cloud Copy Detection

no code implementations3 Oct 2021 Jiaqi Yang, Xuequan Lu, Wenzhi Chen

In this paper, we focus on a fundamental and practical research problem: judging whether a point cloud is plagiarized or copied to another point cloud in the presence of several manipulations (e. g., similarity transformation, smoothing).

Copy Detection

Automated Security Assessment for the Internet of Things

no code implementations9 Sep 2021 Xuanyu Duan, Mengmeng Ge, Triet H. M. Le, Faheem Ullah, Shang Gao, Xuequan Lu, M. Ali Babar

This security model automatically assesses the security of the IoT network by capturing potential attack paths.

3D Face Recognition: A Survey

no code implementations25 Aug 2021 Yaping Jing, Xuequan Lu, Shang Gao

Face recognition is one of the most studied research topics in the community.

Face Recognition

PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation

1 code implementation ICCV 2021 Qiqi Gu, Qianyu Zhou, Minghao Xu, Zhengyang Feng, Guangliang Cheng, Xuequan Lu, Jianping Shi, Lizhuang Ma

Extensive experiments demonstrate that our method can soundly boost the performance on both cross-domain object detection and segmentation for state-of-the-art techniques.

Domain Adaptation Object Detection +1

Image Deformation Estimation via Multi-Objective Optimization

no code implementations8 Jun 2021 Takumi Nakane, Xuequan Lu, Haoran Xie, Chao Zhang

Specifically, by partitioning the template image into several regions and measuring the similarity of each region independently, multiple objectives are built and deformation estimation can thus be realized by solving the MOP with off-the-shelf multi-objective evolutionary algorithms (MOEAs).

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

no code implementations23 Apr 2021 Sheldon Fung, Xuequan Lu, Chao Zhang, Chang-Tsun Li

Extensive experiments show that our unsupervised learning method enables comparable detection performance to state-of-the-art supervised techniques, in both the intra- and inter-dataset settings.

Contrastive Learning DeepFake Detection +1

I-Nema: A Biological Image Dataset for Nematode Recognition

1 code implementation15 Mar 2021 Xuequan Lu, Yihao Wang, Sheldon Fung, Xue Qing

In this paper, we identify two main bottlenecks: (1) the lack of a publicly available imaging dataset for diverse species of nematodes (especially the species only found in natural environment) which requires considerable human resources in field work and experts in taxonomy, and (2) the lack of a standard benchmark of state-of-the-art deep learning techniques on this dataset which demands the discipline background in computer science.

Chaotic-to-Fine Clustering for Unlabeled Plant Disease Images

no code implementations18 Jan 2021 Uno Fang, JianXin Li, Xuequan Lu, Mumtaz Ali, Longxiang Gao, Yong Xiang

Current annotation for plant disease images depends on manual sorting and handcrafted features by agricultural experts, which is time-consuming and labour-intensive.

Deep Detection for Face Manipulation

no code implementations13 Sep 2020 Disheng Feng, Xuequan Lu, Xufeng Lin

It has become increasingly challenging to distinguish real faces from their visually realistic fake counterparts, due to the great advances of deep learning based face manipulation techniques in recent years.

General Classification

Example-based Color Transfer with Gaussian Mixture Modeling

no code implementations31 Aug 2020 Chunzhi Gu, Xuequan Lu, Chao Zhang

In particular, we relate the transferred image with the example image under the Gaussian Mixture Model (GMM) and regard the transferred image color as the GMM centroids.

Deep Patch-based Human Segmentation

no code implementations11 Jul 2020 Dongbo Zhang, Zheng Fang, Xuequan Lu, Hong Qin, Antonio Robles-Kelly, Chao Zhang, Ying He

3D human segmentation has seen noticeable progress in re-cent years.

Scene Image Representation by Foreground, Background and Hybrid Features

no code implementations5 Jun 2020 Chiranjibi Sitaula, Yong Xiang, Sunil Aryal, Xuequan Lu

In this paper, we propose to use hybrid features in addition to foreground and background features to represent scene images.

General Classification

Content and Context Features for Scene Image Representation

no code implementations5 Jun 2020 Chiranjibi Sitaula, Sunil Aryal, Yong Xiang, Anish Basnet, Xuequan Lu

Existing research in scene image classification has focused on either content features (e. g., visual information) or context features (e. g., annotations).

General Classification Image Classification

Spoof Face Detection Via Semi-Supervised Adversarial Training

no code implementations22 May 2020 Chengwei Chen, Wang Yuan, Xuequan Lu, Lizhuang Ma

To capture the underlying structure of live faces data in latent representation space, we propose to train the live face data only, with a convolutional Encoder-Decoder network acting as a Generator.

Face Detection Face Recognition +1

Deep Feature-preserving Normal Estimation for Point Cloud Filtering

no code implementations24 Apr 2020 Dening Lu, Xuequan Lu, Yangxing Sun, Jun Wang

In this paper, we propose a novel feature-preserving normal estimation method for point cloud filtering with preserving geometric features.

SHX: Search History Driven Crossover for Real-Coded Genetic Algorithm

no code implementations30 Mar 2020 Takumi Nakane, Xuequan Lu, Chao Zhang

In evolutionary algorithms, genetic operators iteratively generate new offspring which constitute a potentially valuable set of search history.

Pointfilter: Point Cloud Filtering via Encoder-Decoder Modeling

no code implementations14 Feb 2020 Dongbo Zhang, Xuequan Lu, Hong Qin, Ying He

In this paper, we propose a novel deep learning approach that automatically and robustly filters point clouds with removing noise and preserving sharp features and geometric details.

Graphics

G2MF-WA: Geometric Multi-Model Fitting with Weakly Annotated Data

no code implementations20 Jan 2020 Chao Zhang, Xuequan Lu, Katsuya Hotta, Xi Yang

The WA data can be naturally obtained in an interactive way for specific tasks, for example, in the case of homography estimation, one can easily annotate points on the same plane/object with a single label by observing the image.

Homography Estimation

Unsupervised Deep Features for Privacy Image Classification

no code implementations24 Sep 2019 Chiranjibi Sitaula, Yong Xiang, Sunil Aryal, Xuequan Lu

Sharing images online poses security threats to a wide range of users due to the unawareness of privacy information.

Classification General Classification +1

Tag-based Semantic Features for Scene Image Classification

no code implementations22 Sep 2019 Chiranjibi Sitaula, Yong Xiang, Anish Basnet, Sunil Aryal, Xuequan Lu

In this paper, we introduce novel semantic features of an image based on the annotations and descriptions of its similar images available on the web.

Classification General Classification +2

Explicit Facial Expression Transfer via Fine-Grained Representations

no code implementations6 Sep 2019 Zhiwen Shao, Hengliang Zhu, Junshu Tang, Xuequan Lu, Lizhuang Ma

Instead of using an intermediate estimated guidance, we propose to explicitly transfer facial expression by directly mapping two unpaired input images to two synthesized images with swapped expressions.

Multi-class Classification

Indoor image representation by high-level semantic features

no code implementations12 Jun 2019 Chiranjibi Sitaula, Yong Xiang, Yushu Zhang, Xuequan Lu, Sunil Aryal

Nevertheless, most of the existing feature extraction methods, which extract features based on pixels, color, shape/object parts or objects on images, suffer from limited capabilities in describing semantic information (e. g., object association).

General Classification Image Classification

HLO: Half-kernel Laplacian Operator for Surface Smoothing

1 code implementation12 May 2019 Wei Pan, Xuequan Lu, Yuanhao Gong, Wenming Tang, Jun Liu, Ying He, Guoping Qiu

This paper presents a simple yet effective method for feature-preserving surface smoothing.

Computational Geometry Graphics

A Probabilistic Bitwise Genetic Algorithm for B-Spline based Image Deformation Estimation

no code implementations26 Mar 2019 Takumi Nakane, Takuya Akashi, Xuequan Lu, Chao Zhang

We propose a novel genetic algorithm to solve the image deformation estimation problem by preserving the genetic diversity.

Blur Removal via Blurred-Noisy Image Pair

no code implementations26 Mar 2019 Chunzhi Gu, Xuequan Lu, Ying He, Chao Zhang

Complex blur such as the mixup of space-variant and space-invariant blur, which is hard to model mathematically, widely exists in real images.

Deblurring Image Deblurring +1

Unconstrained Facial Action Unit Detection via Latent Feature Domain

1 code implementation25 Mar 2019 Zhiwen Shao, Jianfei Cai, Tat-Jen Cham, Xuequan Lu, Lizhuang Ma

Due to the combination of source AU-related information and target AU-free information, the latent feature domain with transferred source label can be learned by maximizing the target-domain AU detection performance.

Action Unit Detection Domain Adaptation +2

Blur-Countering Keypoint Detection via Eigenvalue Asymmetry

no code implementations5 Sep 2018 Chao Zhang, Xuequan Lu, Takuya Akashi

To settle this issue, we propose a blur-countering method for detecting valid keypoints for various types and degrees of blurred images.

Keypoint Detection

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