Search Results for author: Runwei Guan

Found 19 papers, 12 papers with code

Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perception

no code implementations26 Jan 2025 Lianqing Zheng, Jianan Liu, Runwei Guan, Long Yang, Shouyi Lu, Yuanzhe Li, Xiaokai Bai, Jie Bai, Zhixiong Ma, Hui-Liang Shen, Xichan Zhu

In this paper, we propose Doracamom, the first framework that fuses multi-view cameras and 4D radar for joint 3D object detection and semantic occupancy prediction, enabling comprehensive environmental perception.

3D Object Detection Autonomous Driving +2

UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detection

no code implementations23 Sep 2024 Haocheng Zhao, Runwei Guan, Taoyu Wu, Ka Lok Man, Limin Yu, Yutao Yue

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.

3D Object Detection Depth Estimation +2

DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving

no code implementations16 Sep 2024 Songning Lai, Tianlang Xue, Hongru Xiao, Lijie Hu, Jiemin Wu, Ninghui Feng, Runwei Guan, Haicheng Liao, Zhenning Li, Yutao Yue

Recent advancements in autonomous driving have seen a paradigm shift towards end-to-end learning paradigms, which map sensory inputs directly to driving actions, thereby enhancing the robustness and adaptability of autonomous vehicles.

Autonomous Driving

NanoMVG: USV-Centric Low-Power Multi-Task Visual Grounding based on Prompt-Guided Camera and 4D mmWave Radar

no code implementations30 Aug 2024 Runwei Guan, Jianan Liu, Liye Jia, Haocheng Zhao, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Eng Gee Lim, Jeremy Smith, Yutao Yue

Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs), yet the high complexity of modern learning-based visual grounding model using multi-sensors prevents such model to be deployed on USVs in the real-life.

Autonomous Driving Visual Grounding

radarODE: An ODE-Embedded Deep Learning Model for Contactless ECG Reconstruction from Millimeter-Wave Radar

1 code implementation3 Aug 2024 Yuanyuan Zhang, Runwei Guan, Lingxiao Li, Rui Yang, Yutao Yue, Eng Gee Lim

Radar-based contactless cardiac monitoring has become a popular research direction recently, but the fine-grained electrocardiogram (ECG) signal is still hard to reconstruct from millimeter-wave radar signal.

Decoder

Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehension

1 code implementation21 May 2024 Runwei Guan, RuiXiao Zhang, Ningwei Ouyang, Jianan Liu, Ka Lok Man, Xiaohao Cai, Ming Xu, Jeremy Smith, Eng Gee Lim, Yutao Yue, Hui Xiong

Moreover, we propose a novel model, T-RadarNet, for 3D REC on point clouds, achieving State-Of-The-Art (SOTA) performance on the Talk2Radar dataset compared to counterparts.

3D visual grounding Referring Expression +1

Referring Flexible Image Restoration

1 code implementation16 Apr 2024 Runwei Guan, Rongsheng Hu, Zhuhao Zhou, Tianlang Xue, Ka Lok Man, Jeremy Smith, Eng Gee Lim, Weiping Ding, Yutao Yue

These situations and requirements shed light on a new challenge in image restoration, where a model must perceive and remove specific degradation types specified by human commands in images with multiple degradations.

Image Restoration

Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalities

1 code implementation14 Dec 2023 Runwei Guan, Haocheng Zhao, Shanliang Yao, Ka Lok Man, Xiaohui Zhu, Limin Yu, Yong Yue, Jeremy Smith, Eng Gee Lim, Weiping Ding, Yutao Yue

Urban water-surface robust perception serves as the foundation for intelligent monitoring of aquatic environments and the autonomous navigation and operation of unmanned vessels, especially in the context of waterway safety.

Autonomous Navigation Multi-Task Learning +5

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

2 code implementations20 Aug 2023 Runwei Guan, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee Lim, Yutao Yue

However, most existing research has primarily focused on fusing visual and radar features dedicated to object detection or utilizing a shared feature space for multiple tasks, neglecting the individual representation differences between various tasks.

Autonomous Navigation object-detection +3

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

1 code implementation14 Jul 2023 Runwei Guan, Shanliang Yao, Xiaohui Zhu, Ka Lok Man, Eng Gee Lim, Jeremy Smith, Yong Yue, Yutao Yue

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 the asynchrony between perception results and USV position, and leading to error decisions of autonomous navigation.

2D Semantic Segmentation Autonomous Navigation +3

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

2 code implementations20 Apr 2023 Shanliang Yao, Runwei Guan, Xiaoyu Huang, Zhuoxiao Li, Xiangyu Sha, Yong Yue, Eng Gee Lim, Hyungjoon Seo, Ka Lok Man, Xiaohui Zhu, Yutao Yue

Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation.

Autonomous Driving object-detection +4

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