92 citations · 134 across the 7 of their papers we have counts for
6 papers · 1 filter
Enhanced Spatiotemporal Consistency for Image-to-LiDAR Data Pretraining
Xiang Xu, Lingdong Kong, Hui Shuai +5
LiDAR representation learning has emerged as a promising approach to reducing reliance on costly and labor-intensive human annotations. While existing methods primarily focus on sp…
PoI: A Filter to Extract Pixel of Interest from Novel Views for Scene Coordinate Regression
Feifei Li, Qi Song, Chi Zhang +2
Neural View Synthesis (NVS) techniques such as NeRF and 3D Gaussian Splatting (3DGS) have enabled photorealistic rendering from novel viewpoints and are increasingly used to augmen…
LiMoE: Mixture of LiDAR Representation Learners from Automotive Scenes
Xiang Xu, Lingdong Kong, Hui Shuai +3
LiDAR data pretraining offers a promising approach to leveraging large-scale, readily available datasets for enhanced data utilization. However, existing methods predominantly focu…
4D Contrastive Superflows are Dense 3D Representation Learners
Xiang Xu, Lingdong Kong, Hui Shuai +5
In the realm of autonomous driving, accurate 3D perception is the foundation. However, developing such models relies on extensive human annotations -- a process that is both costly…
FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation
Xiang Xu, Lingdong Kong, Hui Shuai +1
LiDAR segmentation has become a crucial component of advanced autonomous driving systems. Recent range-view LiDAR segmentation approaches show promise for real-time processing. How…
Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation
Hui Shuai, Lele Wu, Qingshan Liu
This paper proposes a unified framework dubbed Multi-view and Temporal Fusing Transformer (MTF-Transformer) to adaptively handle varying view numbers and video length without camer…