11 citations · 17 across the 15 of their papers we have counts for
11 papers · 1 filter
SFVO: Decoupled Confidence-Guided Stereo-Flow Visual Odometry with Bidirectional PnP
Kai Zhang, Guoyang Zhao, Jun Ma
Deep learning-based visual odometry (VO) has achieved significant progress, yet most existing methods focus on a monocular approach, which suffers from scale ambiguity. Stereo VO p…
Traffic Sign Recognition in Autonomous Driving: Dataset, Benchmark, and Field Experiment
Guoyang Zhao, Weiqing Qi, Kai Zhang +7
Traffic Sign Recognition (TSR) is a core perception capability for autonomous driving, where robustness to cross-region variation, long-tailed categories, and semantic ambiguity is…
Task-Oriented Pre-Training for Drivable Area Detection
Fulong Ma, Guoyang Zhao, Weiqing Qi +2
Pre-training techniques play a crucial role in deep learning, enhancing models' performance across a variety of tasks. By initially training on large datasets and subsequently fine…
Erase, then Redraw: A Novel Data Augmentation Approach for Free Space Detection Using Diffusion Model
Fulong Ma, Weiqing Qi, Guoyang Zhao +2
Data augmentation is one of the most common tools in deep learning, underpinning many recent advances including tasks such as classification, detection, and semantic segmentation.…
TSCLIP: Robust CLIP Fine-Tuning for Worldwide Cross-Regional Traffic Sign Recognition
Guoyang Zhao, Fulong Ma, Weiqing Qi +4
Traffic sign is a critical map feature for navigation and traffic control. Nevertheless, current methods for traffic sign recognition rely on traditional deep learning models, whic…
FisheyeDepth: A Real Scale Self-Supervised Depth Estimation Model for Fisheye Camera
Guoyang Zhao, Yuxuan Liu, Weiqing Qi +3
Accurate depth estimation is crucial for 3D scene comprehension in robotics and autonomous vehicles. Fisheye cameras, known for their wide field of view, have inherent geometric be…
CLRKDNet: Speeding up Lane Detection with Knowledge Distillation
Weiqing Qi, Guoyang Zhao, Fulong Ma +2
Road lanes are integral components of the visual perception systems in intelligent vehicles, playing a pivotal role in safe navigation. In lane detection tasks, balancing accuracy…
Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks
Fulong Ma, Weiqing Qi, Guoyang Zhao +5
3D lane detection is essential in autonomous driving as it extracts structural and traffic information from the road in three-dimensional space, aiding self-driving cars in logical…
OmniColor: A Global Camera Pose Optimization Approach of LiDAR-360Camera Fusion for Colorizing Point Clouds
Bonan Liu, Guoyang Zhao, Jianhao Jiao +6
A Colored point cloud, as a simple and efficient 3D representation, has many advantages in various fields, including robotic navigation and scene reconstruction. This representatio…
CurbNet: Curb Detection Framework Based on LiDAR Point Cloud Segmentation
Guoyang Zhao, Fulong Ma, Weiqing Qi +3
Curb detection is a crucial function in intelligent driving, essential for determining drivable areas on the road. However, the complexity of road environments makes curb detection…
Every Dataset Counts: Scaling up Monocular 3D Object Detection with Joint Datasets Training
Fulong Ma, Xiaoyang Yan, Guoyang Zhao +4
Monocular 3D object detection plays a crucial role in autonomous driving. However, existing monocular 3D detection algorithms depend on 3D labels derived from LiDAR measurements, w…