LiDAR Super-Resolution: Boosting Autonomous Driving with Deep Learning
research#computer vision🔬 Research|Analyzed: Feb 19, 2026 05:03•
Published: Feb 19, 2026 05:00
•1 min read
•ArXiv VisionAnalysis
This paper presents a groundbreaking survey on LiDAR super-resolution, a technology poised to revolutionize autonomous driving. It explores how deep learning enhances sparse LiDAR data to produce high-resolution point clouds, opening the door for more reliable and efficient self-driving systems. This comprehensive review is essential for anyone interested in the future of autonomous vehicles!
Key Takeaways
- •LiDAR super-resolution uses deep learning to improve low-resolution sensor data.
- •The survey categorizes existing methods into CNN-based, model-based, implicit representation, and Transformer/Mamba-based approaches.
- •Real-time inference and cross-sensor generalization are key areas of focus.
Reference / Citation
View Original"This paper presents the first comprehensive survey of LiDAR super-resolution methods for autonomous driving."