Ke-MLS

A large-scale labeled mobile Lidar data set from Indian urban region

Bibliographic Data

ID21248046
AuthorsVaibhav Kumar (0000-0002-0047-0681, Indian Institute of Science Education and Research, Bhopal, corresponding author), Bharat Lohani (0000-0001-8589-192X, Indian Institute of Technology Kanpur), Pyare Lal (0000-0001-9333-2618, Indian Institute of Science Education and Research, Bhopal), Aakash Singh Bais (0000-0003-4549-0018, Indian Institute of Science Education and Research, Bhopal), ADITYA ADITYA (0000-0002-7824-8837, Indian Institute of Technology Kanpur)
Year2026
Publication date2026-03-14
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning B Urban Analytics and City Science (JOURNAL)
Journal identifiersISSN: 2399-8083 • E-ISSN: 2399-8091
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/23998083261430812
OpenAlexW7135396766
LanguageEN
References cited14

Labeled Mobile Laser Scanning (MLS) data are increasingly in demand for applications such as urban planning and autonomous driving. However, there is a severe shortage of manually labeled, high-fidelity MLS datasets, especially from developing countries like India. Deep learning models trained on less complex environments often fail to generalize to Indian scenarios, hindering the development of robust applications. To address this gap, we introduce Ke-MLS, the largest publicly available, expert-labeled MLS LiDAR dataset from Kerala, India. The dataset comprises 48 classes and supports the training of a variety of deep learning models for multiple applications. We evaluate the performance of state-of-the-art 3D deep learning algorithms on Ke-MLS, achieving mean Intersection-Over-Union (mIoU) scores in the range of 70–80%. The dataset is publicly available at https://lidaverse.com

Data set · Deep learning · Economic shortage · Lidar · Training set · Advanced Optical Sensing Technologies · Remote Sensing and LiDAR Applications · Robotics and Sensor-Based Localization

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Open DOI