no code implementations • 26 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.
no code implementations • 17 Jan 2025 • Benjamin Kiefer, Lojze Žust, Jon Muhovič, Matej Kristan, Janez Perš, Matija Teršek, Uma Mudenagudi Chaitra Desai, Arnold Wiliem, Marten Kreis, Nikhil Akalwadi, Yitong Quan, Zhiqiang Zhong, Zhe Zhang, Sujie Liu, Xuran Chen, Yang Yang, Matej Fabijanić, Fausto Ferreira, Seongju Lee, Junseok Lee, Kyoobin Lee, Shanliang Yao, Runwei Guan, Xiaoyu Huang, Yi Ni, Himanshu Kumar, Yuan Feng, Yi-Ching Cheng, Chia-Ming Lee, Jannik Sheikh, Andreas Michel, Wolfgang Gross, Martin Weinmann, Josip Šarić, Yipeng Lin, Xiang Yang, Nan Jiang, Yutang Lu, Fei Feng, Ali Awad, Evan Lucas, Ashraf Saleem, Ching-Heng Cheng, Yu-Fan Lin, Tzu-Yu Lin, Chih-Chung Hsu
The 3rd Workshop on Maritime Computer Vision (MaCVi) 2025 addresses maritime computer vision for Unmanned Surface Vehicles (USV) and underwater.
1 code implementation • 4 Jan 2025 • Liye Jia, Runwei Guan, Haocheng Zhao, Qiuchi Zhao, Ka Lok Man, Jeremy Smith, Limin Yu, Yutao Yue
In this paper, we propose RadarNeXt, a real-time and reliable 3D object detector based on the 4D mmWave radar point clouds.
Ranked #5 on
3D Object Detection (RoI)
on View-of-Delft (val)
no code implementations • 23 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.
no code implementations • 16 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.
no code implementations • 5 Sep 2024 • Bowen Tian, Songning Lai, Lujundong Li, Zhihao Shuai, Runwei Guan, Tian Wu, Yutao Yue
Fine-grained image classification has witnessed significant advancements with the advent of deep learning and computer vision technologies.
no code implementations • 30 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.
1 code implementation • 3 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.
1 code implementation • 21 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.
1 code implementation • 16 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.
no code implementations • 19 Mar 2024 • Runwei Guan, Liye Jia, Fengyufan Yang, Shanliang Yao, Erick Purwanto, Xiaohui Zhu, Eng Gee Lim, Jeremy Smith, Ka Lok Man, Xuming Hu, Yutao Yue
The pattern of text-guided two sensors equips a finer granularity of text prompts with visual and radar features of referred targets.
1 code implementation • 14 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.
2 code implementations • 8 Dec 2023 • Shanliang Yao, Runwei Guan, Zitian Peng, Chenhang Xu, Yilu Shi, Weiping Ding, Eng Gee Lim, Yong Yue, Hyungjoon Seo, Ka Lok Man, Jieming Ma, Xiaohui Zhu, Yutao Yue
This review focuses on exploring different radar data representations utilized in autonomous driving systems.
2 code implementations • 20 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.
1 code implementation • 18 Jul 2023 • Lulu Liu, Runwei Guan, Fei Ma, Jeremy Smith, Yutao Yue
Therefore, interference mitigation is of great significance for millimeter-wave radar-based target detection.
1 code implementation • 14 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.
Ranked #1 on
2D Semantic Segmentation
on WaterScenes
2 code implementations • 13 Jul 2023 • Shanliang Yao, Runwei Guan, Zhaodong Wu, Yi Ni, Zile Huang, Ryan Wen Liu, Yong Yue, Weiping Ding, Eng Gee Lim, Hyungjoon Seo, Ka Lok Man, Jieming Ma, Xiaohui Zhu, Yutao Yue
This work presents WaterScenes, the first multi-task 4D radar-camera fusion dataset for autonomous driving on water surfaces.
Ranked #1 on
Object Detection
on WaterScenes
(using extra training data)
2 code implementations • 21 Apr 2023 • Runwei Guan, Ka Lok Man, Feifan Chen, Shanliang Yao, Rongsheng Hu, Xiaohui Zhu, Jeremy Smith, Eng Gee Lim, Yutao Yue
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.
2 code implementations • 20 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.