24 citations · 61 across the 13 of their papers we have counts for
14 papers
Car-GS: Addressing Reflective and Transparent Surface Challenges in 3D Car Reconstruction
Congcong Li, Jin Wang, Xiaomeng Wang +4
3D car modeling is crucial for applications in autonomous driving systems, virtual and augmented reality, and gaming. However, due to the distinctive properties of cars, such as hi…
Hints of Prompt: Enhancing Visual Representation for Multimodal LLMs in Autonomous Driving
Hao Zhou, Zhanning Gao, Zhili Chen +4
In light of the dynamic nature of autonomous driving environments and stringent safety requirements, general MLLMs combined with CLIP alone often struggle to accurately represent d…
PriorMapNet: Enhancing Online Vectorized HD Map Construction with Priors
Rongxuan Wang, Xin Lu, Xiaoyang Liu +3
Online vectorized High-Definition (HD) map construction is crucial for subsequent prediction and planning tasks in autonomous driving. Following MapTR paradigm, recent works have m…
PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
Zhili Chen, Maosheng Ye, Shuangjie Xu +2
We present a new interaction mechanism of prediction and planning for end-to-end autonomous driving, called PPAD (Iterative Interaction of Prediction and Planning Autonomous Drivin…
SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation
Xuechao Chen, Shuangjie Xu, Xiaoyi Zou +3
LiDAR-based semantic perception tasks are critical yet challenging for autonomous driving. Due to the motion of objects and static/dynamic occlusion, temporal information plays an…
From One to Many: Dynamic Cross Attention Networks for LiDAR and Camera Fusion
Rui Wan, Shuangjie Xu, Wei Wu +2
LiDAR and cameras are two complementary sensors for 3D perception in autonomous driving. LiDAR point clouds have accurate spatial and geometry information, while RGB images provide…
Bootstrap Motion Forecasting With Self-Consistent Constraints
Maosheng Ye, Jiamiao Xu, Xunnong Xu +3
We present a novel framework to bootstrap Motion forecasting with Self-consistent Constraints (MISC). The motion forecasting task aims at predicting future trajectories of vehicles…
Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation
Shuangjie Xu, Rui Wan, Maosheng Ye +2
Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially fo…
DRINet++: Efficient Voxel-as-point Point Cloud Segmentation
Maosheng Ye, Rui Wan, Shuangjie Xu +2
Recently, many approaches have been proposed through single or multiple representations to improve the performance of point cloud semantic segmentation. However, these works do not…
DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation
Maosheng Ye, Shuangjie Xu, Tongyi Cao +1
We present a novel and flexible architecture for point cloud segmentation with dual-representation iterative learning. In point cloud processing, different representations have the…
TPCN: Temporal Point Cloud Networks for Motion Forecasting
Maosheng Ye, Tongyi Cao, Qifeng Chen
We propose the Temporal Point Cloud Networks (TPCN), a novel and flexible framework with joint spatial and temporal learning for trajectory prediction. Unlike existing approaches t…
Provably adaptive reinforcement learning in metric spaces
Tongyi Cao, Akshay Krishnamurthy
We study reinforcement learning in continuous state and action spaces endowed with a metric. We provide a refined analysis of a variant of the algorithm of Sinclair, Banerjee, and…
HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection
Maosheng Ye, Shuangjie Xu, Tongyi Cao
We present Hybrid Voxel Network (HVNet), a novel one-stage unified network for point cloud based 3D object detection for autonomous driving. Recent studies show that 2D voxelizatio…
Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm
Tongyi Cao, Akshay Krishnamurthy
We design new algorithms for the combinatorial pure exploration problem in the multi-arm bandit framework. In this problem, we are given distributions and a collection of subse…