22 citations · 66 across the 11 of their papers we have counts for
11 papers
GSmoothFace: Generalized Smooth Talking Face Generation via Fine Grained 3D Face Guidance
Haiming Zhang, Zhihao Yuan, Chaoda Zheng +6
Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand an…
X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-modal Knowledge Transfer
Linglin Jing, Ying Xue, Xu Yan +7
The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the spars…
LATR: 3D Lane Detection from Monocular Images with Transformer
Yueru Luo, Chaoda Zheng, Xu Yan +4
3D lane detection from monocular images is a fundamental yet challenging task in autonomous driving. Recent advances primarily rely on structural 3D surrogates (e.g., bird's eye vi…
An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
Chaoda Zheng, Xu Yan, Haiming Zhang +4
3D single object tracking in LiDAR point clouds (LiDAR SOT) plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance match…
Benchmarking the Robustness of LiDAR Semantic Segmentation Models
Xu Yan, Chaoda Zheng, Ying Xue +3
When using LiDAR semantic segmentation models for safety-critical applications such as autonomous driving, it is essential to understand and improve their robustness with respect t…
Let Images Give You More:Point Cloud Cross-Modal Training for Shape Analysis
Xu Yan, Heshen Zhan, Chaoda Zheng +4
Although recent point cloud analysis achieves impressive progress, the paradigm of representation learning from a single modality gradually meets its bottleneck. In this work, we t…
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
Xu Yan, Jiantao Gao, Chaoda Zheng +4
As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-mod…
Beyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
Chaoda Zheng, Xu Yan, Haiming Zhang +4
3D single object tracking (3D SOT) in LiDAR point clouds plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching…
PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery
Weibing Zhao, Xu Yan, Jiantao Gao +5
Point Cloud Sampling and Recovery (PCSR) is critical for massive real-time point cloud collection and processing since raw data usually requires large storage and computation. In t…
InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
Zhihao Yuan, Xu Yan, Yinghong Liao +4
Compared with the visual grounding on 2D images, the natural-language-guided 3D object localization on point clouds is more challenging. In this paper, we propose a new model, name…
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion
Xu Yan, Jiantao Gao, Jie Li +4
LiDAR point cloud analysis is a core task for 3D computer vision, especially for autonomous driving. However, due to the severe sparsity and noise interference in the single sweep…