1 code implementation • 18 Sep 2023 • Ting Meng, Chunyun Fu, Mingguang Huang, Xiyang Wang, JiaWei He, Tao Huang, Wankai Shi
However, in terms of the detection confidence fusing classification and localization, objects of low detection confidence may have inaccurate localization but clear appearance; similarly, objects of high detection confidence may have inaccurate localization or unclear appearance; yet these objects are not further classified.
1 code implementation • 18 Apr 2023 • Xiyang Wang, Chunyun Fu, JiaWei He, Mingguang Huang, Ting Meng, Siyu Zhang, Hangning Zhou, Ziyao Xu, Chi Zhang
In the classical tracking-by-detection (TBD) paradigm, detection and tracking are separately and sequentially conducted, and data association must be properly performed to achieve satisfactory tracking performance.
1 code implementation • 3 Mar 2023 • JiaWei He, Chunyun Fu, Xiyang Wang
In the existing literature, most 3D multi-object tracking algorithms based on the tracking-by-detection framework employed deterministic tracks and detections for similarity calculation in the data association stage.
1 code implementation • 24 Feb 2022 • Xiyang Wang, Chunyun Fu, Zhankun Li, Ying Lai, JiaWei He
This association mechanism realizes tracking of an object in a 2D domain when the object is far away and only detected by the camera, and updating of the 2D trajectory with 3D information obtained when the object appears in the LiDAR field of view to achieve a smooth fusion of 2D and 3D trajectories.
Ranked #1 on Multi-Object Tracking on KITTI Tracking test
no code implementations • 8 Aug 2021 • Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker
To mine highly discriminative information from unordered views, HVP performs a novel hierarchical view prediction over a view pair, and aggregates the knowledge learned from the predictions in all view pairs into a global feature.
no code implementations • NAACL (AutoSimTrans) 2021 • Ruiqing Zhang, Xiyang Wang, Chuanqiang Zhang, Zhongjun He, Hua Wu, Zhi Li, Haifeng Wang, Ying Chen, Qinfei Li
This corpus is expected to promote the research of automatic simultaneous translation as well as the development of practical systems.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • ICCV 2019 • Zhizhong Han, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker
To resolve this issue, we propose MAP-VAE to enable the learning of global and local geometry by jointly leveraging global and local self-supervision.
Ranked #15 on 3D Point Cloud Linear Classification on ModelNet40
3D Point Cloud Linear Classification Unsupervised 3D Point Cloud Linear Evaluation
no code implementations • 17 May 2019 • Zhizhong Han, Xiyang Wang, Chi-Man Vong, Yu-Shen Liu, Matthias Zwicker, C. L. Philip Chen
Then, the content and spatial information of each pair of view nodes are encoded by a novel spatial pattern correlation, where the correlation is computed among latent semantic patterns.
no code implementations • 7 Nov 2018 • Zhizhong Han, Mingyang Shang, Xiyang Wang, Yu-Shen Liu, Matthias Zwicker
A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels.