activity
20192022
most citedDynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms

108 citations · 205 across the 15 of their papers we have counts for

collaborators

25 papers

cs.CV2022

Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition

M. Usman Maqbool Bhutta, Yuxiang Sun, Darwin Lau +1

Deep learning-based image retrieval techniques for the loop closure detection demonstrate satisfactory performance. However, it is still challenging to achieve high-level performan…

cs.AI2021

Method for making multi-attribute decisions in wargames by combining intuitionistic fuzzy numbers with reinforcement learning

Yuxiang Sun, Bo Yuan, Yufan Xue +3

Researchers are increasingly focusing on intelligent games as a hot research area.The article proposes an algorithm that combines the multi-attribute management and reinforcement l…

cs.RO20211 cited

On Bundle Adjustment for Multiview PointCloud Registration

Huaiyang Huang, Yuxiang Sun, Jin Wu +5

Multiview registration is used to estimate Rigid Body Transformations (RBTs) from multiple frames and reconstruct a scene with corresponding scans. Despite the success of pairwise…

cs.RO2021

Incorporating Learnt Local and Global Embeddings into Monocular Visual SLAM

Huaiyang Huang, Haoyang Ye, Yuxiang Sun +2

Traditional approaches for Visual Simultaneous Localization and Mapping (VSLAM) rely on low-level vision information for state estimation, such as handcrafted local features or the…

cs.CV20211 cited

CP-loss: Connectivity-preserving Loss for Road Curb Detection in Autonomous Driving with Aerial Images

Zhenhua Xu, Yuxiang Sun, Lujia Wang +1

Road curb detection is important for autonomous driving. It can be used to determine road boundaries to constrain vehicles on roads, so that potential accidents could be avoided. M…

cs.CV2021

Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation

Hengli Wang, Peide Cai, Yuxiang Sun +2

Recently, deep-learning based approaches have achieved impressive performance for autonomous driving. However, end-to-end vision-based methods typically have limited interpretabili…