4 papers
ReaLiTy and LADS: A Unified Framework and Dataset Suite for LiDAR Adaptation Across Sensors and Adverse Weather Conditions
Vivek Anand, Bharat Lohani, Rakesh Mishra +1
Reliable LiDAR perception requires robustness across sensors, environments, and adverse weather. However, existing datasets rarely provide physically consistent observations of the…
Simulating Realistic LiDAR Data Under Adverse Weather for Autonomous Vehicles: A Physics-Informed Learning Approach
Vivek Anand, Bharat Lohani, Rakesh Mishra +1
Accurate LiDAR simulation is crucial for autonomous driving, especially under adverse weather conditions. Existing methods struggle to capture the complex interactions between LiDA…
Benchmarking Deep Learning Architectures for Urban Vegetation Point Cloud Semantic Segmentation from MLS
Aditya Aditya, Bharat Lohani, Jagannath Aryal +1
Vegetation is crucial for sustainable and resilient cities providing various ecosystem services and well-being of humans. However, vegetation is under critical stress with rapid ur…
Toward Physics-Aware Deep Learning Architectures for LiDAR Intensity Simulation
Vivek Anand, Bharat Lohani, Gaurav Pandey +1
Autonomous vehicles (AVs) heavily rely on LiDAR perception for environment understanding and navigation. LiDAR intensity provides valuable information about the reflected laser sig…