lidar
PulseAugur coverage of lidar — every cluster mentioning lidar across labs, papers, and developer communities, ranked by signal.
- 2026-05-18 research_milestone A new method for imaging hidden objects using consumer LiDAR was published. source
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New framework improves autonomous driving perception under sensor failures
Researchers have developed a new framework called Grace-BEV to address the fragility of autonomous driving perception systems when faced with sensor failures. Current multi-modal fusion methods often collapse catastroph…
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New methods tackle 2D-3D cross-modal gait recognition
Two new research papers introduce novel approaches to cross-modal gait recognition, aiming to improve the identification of individuals across different sensing modalities like 2D cameras and 3D LiDAR. DiffCrossGait uti…
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New framework fuses 2D images and 3D LiDAR for better scene perception
Researchers have developed xModel-KD, a novel cross-modal knowledge distillation framework designed to improve 3D point cloud segmentation. This method addresses the limitations of single-modality data by combining the …
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Hesai's lidar sales for robots exceed ADAS for first time
Robotics lidar sales have surpassed ADAS for Hesai Technology in the first quarter of 2026, marking a significant shift in the company's business structure. Hesai reported a 40% year-over-year revenue increase, reaching…
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New pretraining method enhances 3D object detection for autonomous driving
Researchers have developed a new pretraining framework for 3D bird's-eye view object detection, crucial for autonomous driving. This method, called Semantics-Guided Multimodal Masked Autoencoder, uses semantic informati…
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LiDAR glare artifacts tackled with new transient domain method
Researchers have developed a new method to combat internal glare artifacts in solid-state LiDAR sensors, a problem that creates phantom objects and obscures real ones. The proposed solution models this glare as a linear…
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Spiking neural networks achieve energy-efficient LiDAR object detection
Researchers have developed a new spiking neural network (SNN) for object detection in autonomous driving using LiDAR data. This end-to-end network can process bird's eye view representations of point clouds, achieving h…
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Waymo robotaxis struggle with flooded roads, prompting service halts and recall
Waymo's autonomous vehicles have encountered significant issues with flooded roads, leading to service disruptions and a recall for a software update. The self-driving cars have driven into floodwaters and become stuck,…
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New method refines LiDAR-camera calibration using evidence maps
Researchers have developed a new method for calibrating LiDAR and camera systems, particularly for agricultural environments. This approach uses a "support-map-driven" technique to identify which observations are most c…
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New framework generates vehicle LiDAR data from roadside sensors
Researchers have developed RS2AD-LiDAR, a new framework designed to generate vehicle-mounted LiDAR data from roadside sensor observations. This approach aims to overcome the high costs and data limitations associated wi…
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New AI model uses 4D radar for reliable people detection
Researchers have developed a new artificial neural network architecture called TMVA4D, designed for semantic segmentation using 4D radar data. This system is intended to improve the reliability of people detection for a…
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STELLAR model advances autonomous driving perception with 3D data fusion
Researchers have developed STELLAR, a new large model for 3D perception in autonomous driving, by extending a Sparse Window Transformer to integrate LiDAR, radar, camera, and map data. Trained on 50 million driving exam…
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Sensor2Sensor converts dashcam video to AV sensor data
Researchers have developed Sensor2Sensor, a new generative modeling approach to convert in-the-wild dashcam videos into structured, multi-modal sensor data suitable for autonomous driving systems. This method addresses …
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Hybrid ML model improves forest height estimation using satellite data
Researchers have developed a hybrid machine learning model that improves forest height estimation by integrating data from TanDEM-X and Landsat satellites. This enhanced model incorporates optical Landsat data to provid…
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New method uses 3D and 2D AI to estimate wheat spike volume
Researchers have developed a novel hybrid approach to estimate wheat spike volume using a combination of 3D reconstruction and knowledge distillation techniques. This method aims to overcome the challenges of traditiona…
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StruMPL model tackles forest biomass estimation with novel regression techniques
Researchers have developed StruMPL, a novel multi-task dense regression model designed to estimate forest aboveground biomass (AGB) using disparate data sources. The model integrates satellite lidar data, which provides…
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LiDAR motion capture uses Bézier curves for improved accuracy
Researchers have developed a new framework called BMLiCap for more accurate 3D human motion capture using LiDAR data. This method employs Bézier curves to represent motion, which helps in creating a more coherent and le…
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Robots use RGB cameras for 3D scene mapping, improving exploration
Researchers have developed a new framework for 3D scene graph generation that can operate using only RGB cameras, eliminating the need for depth sensors like LiDAR. This approach allows for more flexible deployment on v…
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New learning-based method enhances LiDAR point cloud compression
Researchers have developed Inter-LPCM, a novel learning-based method for compressing LiDAR point cloud data. This approach improves upon existing techniques by utilizing inter-frame prediction to capture complex motion …
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Consumer LiDAR can now image hidden objects using motion-induced sampling
Researchers have developed a new method for imaging objects that are not directly in a device's line of sight, utilizing consumer-grade LiDAR sensors. This technique, called Motion Induced Sampling, overcomes limitation…