no code implementations • 12 Dec 2023 • Haiming Zhang, Zhihao Yuan, Chaoda Zheng, Xu Yan, Baoyuan Wang, Guanbin Li, Song Wu, Shuguang Cui, Zhen Li
Our proposed GSmoothFace model mainly consists of the Audio to Expression Prediction (A2EP) module and the Target Adaptive Face Translation (TAFT) module.
no code implementations • 12 Dec 2023 • Linglin Jing, Ying Xue, Xu Yan, Chaoda Zheng, Dong Wang, Ruimao Zhang, Zhigang Wang, Hui Fang, Bin Zhao, Zhen Li
The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences.
1 code implementation • ICCV 2023 • Yueru Luo, Chaoda Zheng, Xu Yan, Tang Kun, Chao Zheng, Shuguang Cui, Zhen Li
On the one hand, each query is generated based on 2D lane-aware features and adopts a hybrid embedding to enhance lane information.
Ranked #1 on 3D Lane Detection on OpenLane
1 code implementation • 21 Mar 2023 • Chaoda Zheng, Xu Yan, Haiming Zhang, Baoyuan Wang, Shenghui Cheng, Shuguang Cui, Zhen Li
Due to the motion-centric nature, our method shows its impressive generalizability with limited training labels and provides good differentiability for end-to-end cycle training.
1 code implementation • 3 Jan 2023 • Xu Yan, Chaoda Zheng, Ying Xue, Zhen Li, Shuguang Cui, Dengxin Dai
In this paper, we aim to comprehensively analyze the robustness of LiDAR semantic segmentation models under various corruptions.
2 code implementations • 9 Oct 2022 • Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang, Shuguang Cui, Zhen Li
Specifically, this paper introduces a simple but effective point cloud cross-modality training (PointCMT) strategy, which utilizes view-images, i. e., rendered or projected 2D images of the 3D object, to boost point cloud analysis.
Ranked #13 on 3D Point Cloud Classification on ModelNet40
no code implementations • 13 Sep 2022 • Yueru Luo, Xu Yan, Chaoda Zheng, Chao Zheng, Shuqi Mei, Tang Kun, Shuguang Cui, Zhen Li
Estimating accurate lane lines in 3D space remains challenging due to their sparse and slim nature.
Ranked #5 on 3D Lane Detection on OpenLane
1 code implementation • 10 Jul 2022 • Xu Yan, Jiantao Gao, Chaoda Zheng, Chao Zheng, Ruimao Zhang, Shenghui Cui, Zhen Li
As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-modality data fusion.
Ranked #4 on Robust 3D Semantic Segmentation on nuScenes-C
1 code implementation • CVPR 2022 • Chaoda Zheng, Xu Yan, Haiming Zhang, Baoyuan Wang, Shenghui Cheng, Shuguang Cui, Zhen Li
3D single object tracking (3D SOT) in LiDAR point clouds plays a crucial role in autonomous driving.
Ranked #1 on Object Tracking on KITTI
2 code implementations • ICCV 2021 • Chaoda Zheng, Xu Yan, Jiantao Gao, Weibing Zhao, Wei zhang, Zhen Li, Shuguang Cui
Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area.
Ranked #2 on Object Tracking on KITTI
1 code implementation • CVPR 2020 • Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, Shuguang Cui
Extensive experiments verify the robustness and superiority of our approach in point clouds processing tasks regardless of synthesis data, indoor data, and outdoor data with or without noise.
Ranked #27 on Semantic Segmentation on S3DIS