lidar
PulseAugur coverage of lidar — every cluster mentioning lidar across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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TriBand-BEV system achieves real-time LiDAR-only pedestrian detection
Researchers have developed TriBand-BEV, a novel real-time 3D pedestrian detection system using only LiDAR data. The system encodes 3D LiDAR point clouds into a lightweight 2D Bird's Eye View (BEV) tensor with three heig…
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MTA-RL framework enhances urban driving with multi-modal AI
Researchers have developed MTA-RL, a novel framework that integrates multi-modal transformer-based 3D affordances with reinforcement learning for robust urban autonomous driving. This approach fuses RGB images and LiDAR…
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Autonomous driving research tackles adaptive perception and novel adversarial attacks
Researchers have developed an adaptive perception system for autonomous driving that dynamically adjusts its computational resources based on scene complexity, significantly reducing latency without sacrificing accuracy…
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South Korea and MicroVision/Avular advance AI-powered drones for defense
South Korea's National Intelligence Service and military are pooling their data to counter drone threats, integrating AI and real-world training in response to the conflict in Ukraine. In parallel, MicroVision and Avula…
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GEM model generates LiDAR world models for autonomous driving
Researchers have developed GEM, a generative LiDAR world model designed to simulate environmental dynamics for autonomous driving. The model utilizes a deformable Mamba architecture to overcome challenges with disordere…
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AITO M6 integrates advanced Huawei ADS 4.1 and air suspension, offering premium features at a competitive price.
The AITO M6 sedan features advanced Huawei ADS 4.1 intelligent driving system with a high-spec 896-line lidar and 36 sensors across all trims. It also boasts a premium chassis with standard air suspension and CDC damper…
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InterFuserDVS integrates event cameras to enhance autonomous driving safety
Researchers have developed InterFuserDVS, an enhanced sensor fusion model for autonomous driving that integrates Dynamic Vision Sensors (DVS) with traditional RGB cameras and LiDAR. This novel approach uses a token-base…
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HiPR framework improves camera-LiDAR 3D occupancy prediction with height-guided projection
Researchers have introduced HiPR, a novel framework for camera-LiDAR occupancy prediction that addresses limitations in traditional 2D-to-3D view transformations. HiPR utilizes a height-guided projection reparameterizat…
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PROBE descriptor offers robust, learning-free LiDAR place recognition
Researchers have introduced PROBE, a novel learning-free descriptor for LiDAR place recognition. PROBE models Bird's-Eye View (BEV) cell occupancy as a Bernoulli random variable, analytically marginalizing over continuo…
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BEVCALIB model uses bird's-eye view features for LiDAR-camera calibration
Researchers have developed BEVCALIB, a novel method for calibrating LiDAR and camera sensors, crucial for autonomous driving systems. This approach utilizes bird's-eye view (BEV) features extracted from both sensor type…
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Rivian considers in-house lidar production for autonomous vehicles
Rivian's CEO has indicated the company is exploring the production of its own LiDAR sensors for autonomous vehicles. This move suggests a potential shift towards in-house manufacturing for critical self-driving components.
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Rivian considers in-house lidar production for autonomous vehicles
Rivian's CEO has indicated that the electric vehicle company is exploring the possibility of manufacturing its own LiDAR sensors for autonomous driving systems. This potential move aligns with a broader trend of automak…
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PACE model slashes LiDAR point cloud compression latency by 90%
Researchers have introduced PACE, a novel framework designed to significantly improve the efficiency and reduce the latency of LiDAR point cloud compression for autonomous systems. PACE addresses existing bottlenecks by…
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LiDAR-only HD map construction method enhances semantic cues via knowledge distillation
Researchers have developed LIE, a novel method for constructing High-Definition (HD) maps for autonomous driving using only LiDAR data. This approach overcomes the limitations of camera-based methods by leveraging knowl…
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SaLF offers real-time multi-sensor simulation for autonomous driving
Researchers have developed SaLF, a novel volumetric representation for real-time multi-sensor simulation. This method uses a sparse set of 3D voxel primitives, each containing a local implicit field, to achieve faster t…
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AI-powered app translates visual data into auditory feedback for the blind
A new AI-Sight app, also known as SoundSight, has been developed to provide auditory feedback for visually impaired individuals using mobile technology. This application leverages AI models like DeepLabV3, YOLOv5, and Y…
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Car tech innovator discusses self-driving AI, Cybertruck, and future of autonomous vehicles
This podcast episode features a discussion with Ken Smiley, a car-tech builder, about the future of self-driving AI. The conversation touches on topics such as autonomous vehicles, computer vision, and the evolution of …
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Ouster's new color lidar technology promises to revolutionize AI and sensor development
Ouster has introduced new color LiDAR sensors that aim to surpass traditional cameras in various applications. These sensors are expected to usher in a new phase for both artificial intelligence development and sensor t…
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EdgeLPR paper explores neural network precision vs performance trade-offs for LiDAR place recognition
Researchers have developed EdgeLPR, a method for efficient LiDAR-based place recognition on edge devices. The approach utilizes Bird's Eye View representations to enable lightweight image-based networks for autonomous n…
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Researchers introduce APCoTTA for continuous adaptation of LiDAR point cloud segmentation models.
Researchers have introduced APCoTTA, a new framework designed for continuous test-time adaptation in semantic segmentation of airborne LiDAR point clouds. This method addresses performance degradation in deployed models…