activity
20192023
most citedTrajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline

82 citations · 143 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

9 papers · 1 filter

cs.CV2023

Density-invariant Features for Distant Point Cloud Registration

Quan Liu, Hongzi Zhu, Yunsong Zhou +3

Registration of distant outdoor LiDAR point clouds is crucial to extending the 3D vision of collaborative autonomous vehicles, and yet is challenging due to small overlapping area…

cs.CV2023★ 1 cited

Scene as Occupancy

Chonghao Sima, Wenwen Tong, Tai Wang +8

Human driver can easily describe the complex traffic scene by visual system. Such an ability of precise perception is essential for driver's planning. To achieve this, a geometry-a…

cs.RO2023★ 22 cited

End-to-end Autonomous Driving: Challenges and Frontiers

Li Chen, Penghao Wu, Kashyap Chitta +3

The autonomous driving community has witnessed a rapid growth in approaches that embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle motion pl…

cs.CV2023

Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving

Xiaosong Jia, Penghao Wu, Li Chen +4

End-to-end autonomous driving has made impressive progress in recent years. Existing methods usually adopt the decoupled encoder-decoder paradigm, where the encoder extracts hidden…

cs.CV2023★ 1 cited

Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation

Shilin Yan, Renrui Zhang, Ziyu Guo +7

Recently, video object segmentation (VOS) referred by multi-modal signals, e.g., language and audio, has evoked increasing attention in both industry and academia. It is challengin…

cs.CV2023★ 5 cited

Geometric-aware Pretraining for Vision-centric 3D Object Detection

Linyan Huang, Huijie Wang, Jia Zeng +4

Multi-camera 3D object detection for autonomous driving is a challenging problem that has garnered notable attention from both academia and industry. An obstacle encountered in vis…

cs.CV2023

Graph-based Topology Reasoning for Driving Scenes

Tianyu Li, Li Chen, Huijie Wang +10

Understanding the road genome is essential to realize autonomous driving. This highly intelligent problem contains two aspects - the connection relationship of lanes, and the assig…

cs.CV2023★ 2 cited

3D Data Augmentation for Driving Scenes on Camera

Wenwen Tong, Jiangwei Xie, Tianyu Li +7

Driving scenes are extremely diverse and complicated that it is impossible to collect all cases with human effort alone. While data augmentation is an effective technique to enrich…

cs.CV2023★ 7 cited

Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling

Penghao Wu, Li Chen, Hongyang Li +3

Witnessing the impressive achievements of pre-training techniques on large-scale data in the field of computer vision and natural language processing, we wonder whether this idea c…