no code implementations • 11 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.
no code implementations • 15 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.
no code implementations • 20 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.
no code implementations • 13 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.
1 code implementation • 17 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.
no code implementations • 29 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.
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.
1 code implementation • CVPR 2023 • Xinjiang Wang, Zeyu Liu, Yu Hu, Wei Xi, Wenxian Yu, Danping Zou
We introduce a lightweight network to improve descriptors of keypoints within the same image.
no code implementations • 16 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.
no code implementations • 14 Apr 2022 • Shenghan Su, Ziteng Cui, Weiwei Guo, Zenghui Zhang, Wenxian Yu
Deep learning methods exhibit outstanding performance in synthetic aperture radar (SAR) image interpretation tasks.
2 code implementations • 19 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.
1 code implementation • ICCV 2021 • Boying Li, Yuan Huang, Zeyu Liu, Danping Zou, Wenxian Yu
Inspired by the early works on indoor modeling, we leverage the structural regularities exhibited in indoor scenes, to train a better depth network.
1 code implementation • 2 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.
no code implementations • 20 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.
1 code implementation • 15 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.
no code implementations • 4 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.
1 code implementation • 26 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.
no code implementations • 9 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.
no code implementations • 16 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.
Robotics