Search Results for author: Wenxian Yu

Found 19 papers, 8 papers with code

Stereo-LiDAR Depth Estimation with Deformable Propagation and Learned Disparity-Depth Conversion

no code implementations11 Apr 2024 Ang Li, Anning Hu, Wei Xi, Wenxian Yu, Danping Zou

To address this issue, we propose a novel stereo-LiDAR depth estimation network with Semi-Dense hint Guidance, named SDG-Depth.

Depth Estimation Stereo Matching

Thermal-NeRF: Neural Radiance Fields from an Infrared Camera

no code implementations15 Mar 2024 Tianxiang Ye, Qi Wu, Junyuan Deng, Guoqing Liu, Liu Liu, Songpengcheng Xia, Liang Pang, Wenxian Yu, Ling Pei

In recent years, Neural Radiance Fields (NeRFs) have demonstrated significant potential in encoding highly-detailed 3D geometry and environmental appearance, positioning themselves as a promising alternative to traditional explicit representation for 3D scene reconstruction.

3D Scene Reconstruction

Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learning

no code implementations20 Nov 2023 Yan Li, Weiwei Guo, Xue Yang, Ning Liao, Dunyun He, Jiaqi Zhou, Wenxian Yu

In this paper, we aim to develop open-vocabulary object detection (OVD) technique in aerial images that scales up object vocabulary size beyond training data.

Object object-detection +3

Timestamp-supervised Wearable-based Activity Segmentation and Recognition with Contrastive Learning and Order-Preserving Optimal Transport

no code implementations13 Oct 2023 Songpengcheng Xia, Lei Chu, Ling Pei, Jiarui Yang, Wenxian Yu, Robert C. Qiu

To address these challenges, we propose a novel method for joint activity segmentation and recognition with timestamp supervision, in which only a single annotated sample is needed in each activity segment.

Contrastive Learning Human Activity Recognition +1

TextSLAM: Visual SLAM with Semantic Planar Text Features

1 code implementation17 May 2023 Boying Li, Danping Zou, Yuan Huang, Xinghan Niu, Ling Pei, Wenxian Yu

The results show that integrating texture features leads to a more superior SLAM system that can match images across day and night.

Mixed Reality Scene Understanding

Sparsity-Aware Optimal Transport for Unsupervised Restoration Learning

no code implementations29 Apr 2023 Fei Wen, Wei Wang, Wenxian Yu

Recent studies show that, without any prior model, the unsupervised restoration learning problem can be optimally formulated as an optimal transport (OT) problem, which has shown promising performance on denoising tasks to approach the performance of supervised methods.

Denoising Rain Removal +1

NeRF-LOAM: Neural Implicit Representation for Large-Scale Incremental LiDAR Odometry and Mapping

1 code implementation ICCV 2023 Junyuan Deng, Xieyuanli Chen, Songpengcheng Xia, Zhen Sun, Guoqing Liu, Wenxian Yu, Ling Pei

To bridge this gap, in this paper, we propose a novel NeRF-based LiDAR odometry and mapping approach, NeRF-LOAM, consisting of three modules neural odometry, neural mapping, and mesh reconstruction.

Multi-level Contrast Network for Wearables-based Joint Activity Segmentation and Recognition

no code implementations16 Aug 2022 Songpengcheng Xia, Lei Chu, Ling Pei, Wenxian Yu, Robert C. Qiu

Human activity recognition (HAR) with wearables is promising research that can be widely adopted in many smart healthcare applications.

Activity Prediction Human Activity Recognition +1

M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots

2 code implementations19 Dec 2021 Jie Yin, Ang Li, Tao Li, Wenxian Yu, Danping Zou

We introduce M2DGR: a novel large-scale dataset collected by a ground robot with a full sensor-suite including six fish-eye and one sky-pointing RGB cameras, an infrared camera, an event camera, a Visual-Inertial Sensor (VI-sensor), an inertial measurement unit (IMU), a LiDAR, a consumer-grade Global Navigation Satellite System (GNSS) receiver and a GNSS-IMU navigation system with real-time kinematic (RTK) signals.

A Pose-only Solution to Visual Reconstruction and Navigation

1 code implementation2 Mar 2021 Qi Cai, Lilian Zhang, Yuanxin Wu, Wenxian Yu, Dewen Hu

Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment.

3D Scene Reconstruction Computational Efficiency +2

MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model

no code implementations20 Sep 2020 Ling Pei, Songpengcheng Xia, Lei Chu, Fanyi Xiao, Qi Wu, Wenxian Yu, Robert Qiu

Together with the rapid development of the Internet of Things (IoT), human activity recognition (HAR) using wearable Inertial Measurement Units (IMUs) becomes a promising technology for many research areas.

Human Activity Recognition Transfer Learning

Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze

1 code implementation15 Sep 2020 Jinquan Li, Ling Pei, Danping Zou, Songpengcheng Xia, Qi Wu, Tao Li, Zhen Sun, Wenxian Yu

This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model (SalNavNet) with traditional monocular visual SLAM.

Simultaneous Localization and Mapping

A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors

no code implementations4 Mar 2020 Fanyi Xiao, Ling Pei, Lei Chu, Danping Zou, Wenxian Yu, Yifan Zhu, Tao Li

The experimental results show that the proposed method can surprisingly converge in a few iterations and achieve an accuracy of 91. 15% on a real IMU dataset, demonstrating the efficiency and effectiveness of the proposed method.

Human Activity Recognition Transfer Learning

TextSLAM: Visual SLAM with Planar Text Features

1 code implementation26 Nov 2019 Boying Li, Danping Zou, Daniele Sartori, Ling Pei, Wenxian Yu

We propose to integrate text objects in man-made scenes tightly into the visual SLAM pipeline.

Scene Understanding

General Method for Prime-point Cyclic Convolution over the Real Field

no code implementations9 May 2019 Qi Cai, Tsung-Ching Lin, Yuanxin Wu, Wenxian Yu, Trieu-Kien Truong

A general and fast method is conceived for computing the cyclic convolution of n points, where n is a prime number.

StructVIO : Visual-inertial Odometry with Structural Regularity of Man-made Environments

no code implementations16 Oct 2018 Danping Zou, Yuanxin Wu, Ling Pei, Haibin Ling, Wenxian Yu

Instead of using Manhattan world assumption, we use Atlanta world model to describe such regularity.


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