no code implementations • 8 May 2024 • Bing Zhu, Zixin He, Weiyi Xiong, Guanhua Ding, Jianan Liu, Tao Huang, Wei Chen, Wei Xiang
However, mmWave radar relies on the collection of reflected signals from the target, and the radar signals containing information is difficult to be fully applied.
no code implementations • 26 Apr 2024 • Zhenrong Zhang, Jianan Liu, Xi Zhou, Tao Huang, Qing-Long Han, Jingxin Liu, Hongbin Liu
Cooperative perception is essential to enhance the efficiency and safety of future transportation systems, requiring extensive data sharing among vehicles on the road, which raises significant privacy concerns.
no code implementations • 11 Mar 2024 • Guanhua Ding, Jianan Liu, Yuxuan Xia, Tao Huang, Bing Zhu, Jinping Sun
Simulation results illustrate the superior estimation accuracy of the proposed PMRA-PMBM filter in terms of both positions and extents of the vehicles comparing with PMBM filters using the gamma Gaussian inverse Wishart and DRA implementations.
no code implementations • 10 Nov 2023 • Jianan Liu, Chunguang Li
Additionally, in the t-SVD framework, the multi-rank of a tensor can describe more fine-grained low-rank structure in the tensor compared with the tubal rank.
no code implementations • 24 Oct 2023 • Hao Li, Quanwei Liu, Jianan Liu, Xiling Liu, Yanni Dong, Tao Huang, Zhihan Lv
To this end, we propose an unpaired MRI SR approach that employs contrastive learning to enhance SR performance with limited HR training data.
no code implementations • 5 Oct 2023 • Tao Huang, Jianan Liu, Xi Zhou, Dinh C. Nguyen, Mostafa Rahimi Azghadi, Yuxuan Xia, Qing-Long Han, Sumei Sun
To address this gap, this paper provides a comprehensive overview of the evolution of CP technologies, spanning from early explorations to recent developments, including advancements in V2X communication technologies.
no code implementations • 12 Sep 2023 • Hao Li, Yusheng Zhou, Jianan Liu, Xiling Liu, Tao Huang, Zhihan Lv, Weidong Cai
Our approach represents reconstructed fully-sampled images as functions of voxel coordinates and prior feature vectors from undersampled images, addressing the generalization challenges of INR.
no code implementations • 12 Sep 2023 • Jianan Liu, Guanhua Ding, Yuxuan Xia, Jinping Sun, Tao Huang, Lihua Xie, Bing Zhu
These provide the first benchmark and important insights for the future development of 4D imaging radar-based online 3D MOT algorithms.
no code implementations • 19 Aug 2023 • Zhenrong Zhang, Jianan Liu, Yuxuan Xia, Tao Huang, Qing-Long Han, Hongbin Liu
The state-of-the-art approaches usually employ a tracking-by-detection method, and data association plays a critical role.
no code implementations • 20 Jul 2023 • Jianan Liu, Qiuchi Zhao, Weiyi Xiong, Tao Huang, Qing-Long Han, Bing Zhu
Additionally, KDE helps alleviate point cloud sparsity by capturing density features.
no code implementations • 3 Jul 2023 • Weiyi Xiong, Jianan Liu, Tao Huang, Qing-Long Han, Yuxuan Xia, Bing Zhu
They are sent to the core of LXL, called "radar occupancy-assisted depth-based sampling", to aid image view transformation.
no code implementations • 4 Jan 2023 • Yusheng Zhou, Hao Li, Jianan Liu, Zhengmin Kong, Tao Huang, Euijoon Ahn, Zhihan Lv, Jinman Kim, David Dagan Feng
Our results substantiate the potential of UNAEN as a promising solution applicable in real-world clinical environments, with the capability to enhance diagnostic accuracy and facilitate image-guided therapies.
no code implementations • 11 Nov 2022 • Yanlong Yang, Jianan Liu, Tao Huang, Qing-Long Han, Gang Ma, Bing Zhu
Recent state-of-the-art works reveal that the fusion of radar and LiDAR can lead to robust detection in adverse weather.
1 code implementation • 21 Jun 2022 • Jianan Liu, Liping Bai, Yuxuan Xia, Tao Huang, Bing Zhu, Qing-Long Han
The global nearest neighbor (GNN) filter, as the earliest random vector-based Bayesian tracking framework, has been adopted in most of state-of-the-arts trackers in the automotive industry.
no code implementations • 13 May 2022 • Jianan Liu, Hao Li, Tao Huang, Euijoon Ahn, Kang Han, Adeel Razi, Wei Xiang, Jinman Kim, David Dagan Feng
However, the difference in degradation representations between synthetic and authentic LR images suppresses the quality of SR images reconstructed from authentic LR images.
no code implementations • 13 Mar 2022 • Weiyi Xiong, Jianan Liu, Yuxuan Xia, Tao Huang, Bing Zhu, Wei Xiang
Deep learning-based instance segmentation enables real-time object identification from the radar detection points.
no code implementations • 10 Mar 2022 • Sulong Ge, Zhihua Xia, Yao Tong, Jian Weng, Jianan Liu
By applying this scheme, when the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the captured photographs.
no code implementations • CVPR 2022 • Qiang Zhang, Changzhou Lai, Jianan Liu, Nianchang Huang, Jungong Han
Then, a feature-level modality compensation module is present to generate those missing modality-specific features from existing modality-shared ones.
no code implementations • 28 Nov 2021 • Hao Li, Jianan Liu
We also analyzed several down-sampling strategies based on the acceleration factor, including multiple combinations of in-plane and through-plane down-sampling, and developed a controllable and quantifiable motion artifact generation method.
no code implementations • 5 Oct 2021 • Jianan Liu, Weiyi Xiong, Liping Bai, Yuxuan Xia, Tao Huang, Wanli Ouyang, Bing Zhu
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the sparsity of radar detection points.
no code implementations • 23 Apr 2021 • Nianchang Huang, Jianan Liu, Qiang Zhang, Jungong Han
Most existing cross-modality person re-identification works rely on discriminative modality-shared features for reducing cross-modality variations and intra-modality variations.
Cross-Modality Person Re-identification Person Re-Identification
2 code implementations • MIDL 2019 • Jun Ma, Zhan Wei, Yiwen Zhang, Yixin Wang, Rongfei Lv, Cheng Zhu, Gaoxiang Chen, Jianan Liu, Chao Peng, Lei Wang, Yunpeng Wang, Jianan Chen
The \emph{second contribution} is that we systematically evaluated five benchmark methods on two representative public datasets.