activity
20202022
most citedNTU VIRAL: A Visual-Inertial-Ranging-Lidar Dataset, From an Aerial Vehicle Viewpoint

188 citations · 346 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2022

SLICT: Multi-input Multi-scale Surfel-Based Lidar-Inertial Continuous-Time Odometry and Mapping

Thien-Minh Nguyen, Daniel Duberg, Patric Jensfelt +2

While feature association to a global map has significant benefits, to keep the computations from growing exponentially, most lidar-based odometry and mapping methods opt to associ…

cs.LG202215 cited

Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors

Jianfei Yang, Xiangyu Peng, Kai Wang +4

Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain. It does not req…

cs.RO20225 cited

Multi-modal Semantic SLAM for Complex Dynamic Environments

Han Wang, Jing Ying Ko, Lihua Xie

Simultaneous Localization and Mapping (SLAM) is one of the most essential techniques in many real-world robotic applications. The assumption of static environments is common in mos…

cs.CV2022137 cited

Computer Vision for Road Imaging and Pothole Detection: A State-of-the-Art Review of Systems and Algorithms

Nachuan Ma, Jiahe Fan, Wenshuo Wang +4

Computer vision algorithms have been prevalently utilized for 3-D road imaging and pothole detection for over two decades. Nonetheless, there is a lack of systematic survey article…

cs.RO2022188 cited

NTU VIRAL: A Visual-Inertial-Ranging-Lidar Dataset, From an Aerial Vehicle Viewpoint

Thien-Minh Nguyen, Shenghai Yuan, Muqing Cao +3

In recent years, autonomous robots have become ubiquitous in research and daily life. Among many factors, public datasets play an important role in the progress of this field, as t…

cs.CV20211 cited

Self-Supervised Video Representation Learning by Video Incoherence Detection

Haozhi Cao, Yuecong Xu, Jianfei Yang +4

This paper introduces a novel self-supervised method that leverages incoherence detection for video representation learning. It roots from the observation that visual systems of hu…