activity
20242026
most citedPEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning

4 citations · 4 across the 3 of their papers we have counts for

collaborators
Showing cs.CVShow all

14 papers · 1 filter

cs.CV20264 cited

PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning

Bowen Tian, Songning Lai, Lujundong Li +4

Fine-grained image classification has witnessed significant advancements with the advent of deep learning and computer vision technologies. However, the scarcity of detailed annota…

cs.CV2026

WaterVideoQA: ASV-Centric Perception and Rule-Compliant Reasoning via Multi-Modal Agents

Runwei Guan, Shaofeng Liang, Ningwei Ouyang +9

While autonomous navigation has achieved remarkable success in passive perception (e.g., object detection and segmentation), it remains fundamentally constrained by a void in knowl…

cs.CV2026

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

Lianqing Zheng, Jianan Liu, Runwei Guan +8

3D object detection and occupancy prediction are critical tasks in autonomous driving, attracting significant attention. Despite the potential of recent vision-based methods, they…

cs.CV2025

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…

cs.CV2025

Da Yu: Towards USV-Based Image Captioning for Waterway Surveillance and Scene Understanding

Runwei Guan, Ningwei Ouyang, Tianhao Xu +10

Automated waterway environment perception is crucial for enabling unmanned surface vessels (USVs) to understand their surroundings and make informed decisions. Most existing waterw…

cs.CV2025

USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways

Shanliang Yao, Runwei Guan, Yi Ni +4

Object tracking in inland waterways plays a crucial role in safe and cost-effective applications, including waterborne transportation, sightseeing tours, environmental monitoring a…