most citedRadar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

246 citations · 261 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

ASY-VRNet: Waterway Panoptic Driving Perception Model based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar

Runwei Guan, Shanliang Yao, Xiaohui Zhu +5

Panoptic Driving Perception (PDP) is critical for the autonomous navigation of Unmanned Surface Vehicles (USVs). A PDP model typically integrates multiple tasks, necessitating the…

cs.CV2023★ 1 cited

Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar

Runwei Guan, Shanliang Yao, Xiaohui Zhu +5

Current perception models for different tasks usually exist in modular forms on Unmanned Surface Vehicles (USVs), which infer extremely slowly in parallel on edge devices, causing…

cs.CV2023★ 5 cited

WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

Shanliang Yao, Runwei Guan, Zhaodong Wu +11

Autonomous driving on water surfaces plays an essential role in executing hazardous and time-consuming missions, such as maritime surveillance, survivors rescue, environmental moni…

cs.CV2023

FindVehicle and VehicleFinder: A NER dataset for natural language-based vehicle retrieval and a keyword-based cross-modal vehicle retrieval system

Runwei Guan, Ka Lok Man, Feifan Chen +6

Natural language (NL) based vehicle retrieval is a task aiming to retrieve a vehicle that is most consistent with a given NL query from among all candidate vehicles. Because NL que…

cs.CV2023★ 246 cited

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Xiaoyu Huang +8

Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surround…

cs.LG2023★ 7 cited

Continual Graph Learning: A Survey

Qiao Yuan, Sheng-Uei Guan, Pin Ni +4

Continual Graph Learning (CGL) enables models to incrementally learn from streaming graph-structured data without forgetting previously acquired knowledge. Experience replay is a c…

cs.IT2022★ 1 cited

Quantify the Causes of Causal Emergence: Critical Conditions of Uncertainty and Asymmetry in Causal Structure

Liye Jia, Fengyufan Yang, Ka Lok Man +4

Beneficial to advanced computing devices, models with massive parameters are increasingly employed to extract more information to enhance the precision in describing and predicting…