3 citations · 4 across the 12 of their papers we have counts for
13 papers
Answer with Evidence: Consistency-Aware Grounded Visual Question Answering for Roadside Traffic Scenes
Runwei Guan, Rongsheng Hu, Shangshu Chen +10
Roadside traffic reasoning requires every free-form textual claim to be backed by visual evidence. Existing grounded multimodal large language models (MLLMs) frequently exhibit say…
Forbid Your Attention: Fooling Multimodal Large Language Models by Selectively Removing Intrinsic Focus in Spectral Domain
Daizong Liu, Junhao Dong, Zhiyuan Ma +6
Multimodal large language models (MLLMs) have extended the capability of large language models (LLMs) to process more contextual multimodal information, showing remarkable progress…
When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking
Shaofeng Liang, Runwei Guan, Wenshuo Chen +7
Resource constraints on UAV platforms have driven a paradigm shift in aerial tracking, from pursuing performance toward balancing accuracy with efficiency. Adaptive Transformer Tra…
Talk2Sensors: 3D Visual Grounding in Autonomous Driving via Sensor-Adaptive Physical Cue Matching
Runwei Guan, Di Tian, Ningwei Ouyang +9
As a key capability for embodied intelligence, 3D visual grounding (3DVG) has been predominantly studied in indoor scenes with RGB-D or point-cloud inputs, while existing outdoor e…
Deep Learning for Semen Analysis in Male Infertility: Computer Vision, Multimodal Fusion, and Clinical Translation
Runwei Guan, Shaofeng Liang, Jiacheng Weng +10
Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and assisted reproductive technolo…
Tactile-based Multimodal Fusion in Embodied Intelligence: A Survey of Vision, Language, and Contact-Driven Paradigms
Zhixiang Cao, Di Tian, Runwei Guan +11
Tactile sensing is a fundamental modality for embodied intelligence, offering unique and direct feedback on contact geometry, material properties, and interaction dynamics that rem…
HyperDet: 3D Object Detection with Hyper 4D Radar Point Clouds
Yichun Xiao, Runwei Guan, Jin Jin +1
How far can 3D object detection go using 4D radar alone? Despite offering weather-robust and velocity- aware sensing for autonomous perception, modern 4D radar still yields sparse,…
Wavelet-based Multi-View Fusion of 4D Radar Tensor and Camera for Robust 3D Object Detection
Runwei Guan, Jianan Liu, Shaofeng Liang +7
4D millimeter-wave (mmWave) radar has been widely adopted in autonomous driving and robot perception due to its low cost and all-weather robustness. However, point-cloud-based rada…
MMDrive: Interactive Scene Understanding Beyond Vision with Multi-representational Fusion
Minghui Hou, Wei-Hsing Huang, Shaofeng Liang +5
Vision-language models enable the understanding and reasoning of complex traffic scenarios through multi-source information fusion, establishing it as a core technology for autonom…
CornerPoint3D: Look at the Nearest Corner Instead of the Center
Ruixiao Zhang, Runwei Guan, Xiangyu Chen +2
3D object detection aims to predict object centers, dimensions, and rotations from LiDAR point clouds. Despite its simplicity, LiDAR captures only the near side of objects, making…
OptiPMB: Enhancing 3D Multi-Object Tracking with Optimized Poisson Multi-Bernoulli Filtering
Guanhua Ding, Yuxuan Xia, Runwei Guan +5
Accurate 3D multi-object tracking (MOT) is crucial for autonomous driving, as it enables robust perception, navigation, and planning in complex environments. While deep learning-ba…
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…