246 citations · 408 across the 26 of their papers we have counts for
16 papers · 1 filter
RoadSceneVQA: Benchmarking Visual Question Answering in Roadside Perception Systems for Intelligent Transportation System
Runwei Guan, Rongsheng Hu, Shangshu Chen +10
Current roadside perception systems mainly focus on instance-level perception, which fall short in enabling interaction via natural language and reasoning about traffic behaviors i…
Cognitive Disentanglement for Referring Multi-Object Tracking
Shaofeng Liang, Runwei Guan, Wangwang Lian +6
As a significant application of multi-source information fusion in intelligent transportation perception systems, Referring Multi-Object Tracking (RMOT) involves localizing and tra…
Talk2PC: Enhancing 3D Visual Grounding through LiDAR and Radar Point Clouds Fusion for Autonomous Driving
Runwei Guan, Jianan Liu, Ningwei Ouyang +8
Embodied outdoor scene understanding forms the foundation for autonomous agents to perceive, analyze, and react to dynamic driving environments. However, existing 3D understanding…
RadarNeXt: Real-Time and Reliable 3D Object Detector Based On 4D mmWave Imaging Radar
Liye Jia, Runwei Guan, Haocheng Zhao +5
3D object detection is crucial for Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS). However, most 3D detectors prioritize detection accuracy, often overlookin…
UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detection
Haocheng Zhao, Runwei Guan, Taoyu Wu +3
4D millimeter-wave (MMW) radar, which provides both height information and dense point cloud data over 3D MMW radar, has become increasingly popular in 3D object detection. In rece…
NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar
Runwei Guan, Jianan Liu, Liye Jia +7
Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs),…
Referring Flexible Image Restoration
Runwei Guan, Rongsheng Hu, Zhuhao Zhou +6
In reality, images often exhibit multiple degradations, such as rain and fog at night (triple degradations). However, in many cases, individuals may not want to remove all degradat…
WaterVG: Waterway Visual Grounding based on Text-Guided Vision and mmWave Radar
Runwei Guan, Liye Jia, Fengyufan Yang +8
The perception of waterways based on human intent is significant for autonomous navigation and operations of Unmanned Surface Vehicles (USVs) in water environments. Inspired by vis…
Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalities
Runwei Guan, Haocheng Zhao, Shanliang Yao +8
Urban water-surface robust perception serves as the foundation for intelligent monitoring of aquatic environments and the autonomous navigation and operation of unmanned vessels, e…
Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review
Shanliang Yao, Runwei Guan, Zitian Peng +10
With the rapid advancements of sensor technology and deep learning, autonomous driving systems are providing safe and efficient access to intelligent vehicles as well as intelligen…
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…
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…
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…
Self-Supervised Learning for Point Clouds Data: A Survey
Changyu Zeng, Wei Wang, Anh Nguyen +1
3D point clouds are a crucial type of data collected by LiDAR sensors and widely used in transportation applications due to its concise descriptions and accurate localization. Deep…
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…
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…