NAVER CORPORATION

Methods and apparatus for detecting objects and determining their three-dimensional position and orientation (pose) using imagery or point cloud data, often for navigation, surveying, or environmental understanding.

Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.

Methods and systems for improving the quality of video streams, generating intermediate frames, or continuously locating and following objects within a sequence of images, even under occlusion.

Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.

Algorithms and systems for generating, optimizing, and executing trajectories for autonomous vehicles or robots to move through an environment, often involving obstacle avoidance, route validation, and goal reaching.

Algorithms and hardware optimizations for rapidly identifying and characterizing relevant visual features (e.g., objects, motion, gradients) from images or video streams, often integrating machine learning for feature representation and recognition, with a focus on real-time performance and reduced computational cost.

Development and optimization of novel neural network layers or architectures specifically designed to improve performance or efficiency for computer vision tasks.

Techniques for combining data from disparate sensor types (e.g., cameras, radar, mobile device signals) to achieve a more robust and comprehensive understanding of an environment or subject, often leveraging machine learning for interpretation and correlation.

Systems that use user data, preferences, and machine learning to generate tailored advice, product recommendations, goal-setting plans, or contextual information for individuals across different domains.

Technologies for generating artificial speech that is personalized, context-aware, or adaptable to specific virtual agents or messaging campaigns, often utilizing text-to-speech (TTS) and audio caching for efficient delivery.

Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.

Methods and systems for monitoring the operational status, detecting anomalies, ensuring safe interaction, and preventing damage or injury in robotic systems.

Techniques and hardware for autonomous systems to gather and interpret data about their surroundings, including obstacle detection, object recognition, and depth estimation, to inform control decisions.

Techniques utilizing deep learning models like Generative Adversarial Networks (GANs) or diffusion models to create new images, modify existing ones, or generate synthetic data based on various inputs or conditions.

Techniques for enhancing, encoding, decoding, or separating speech and audio signals, often involving multi-microphone arrays, acoustic echo cancellation, beamforming, or advanced audio compression for improved clarity and quality.

Design and control of advanced robotic grippers, tools, and mechanical linkages for specific manipulation tasks or operating in challenging environments.

Techniques for generating, updating, and utilizing highly detailed digital maps that include lane-specific information, and for precisely determining a vehicle's position within these lanes, often using sensor data.

Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.

Methods and systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.

Methods and systems for identifying synthetic or manipulated speech (deepfake audio) using forensic analysis of audio features, such as breath patterns, vocoder signatures, or machine learning models to determine authenticity.

Systems and methods that leverage location data, IoT sensors, and predictive analytics to optimize urban services such as traffic flow, emergency response, parking, and waste collection.

Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.

Methods and systems for managing the interaction, communication, and collaborative tasks among multiple autonomous entities, or between autonomous entities and a central control system or users.

AI systems designed to engage in natural language dialogue, maintain conversation state, understand user intent, and generate relevant responses, often across multiple communication channels or modalities.

Technologies for generating and utilizing detailed spatial maps within confined or structured environments like care facilities, construction sites, or industrial warehouses, often for robot navigation or asset tracking.

Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.

Processes for creating or manipulating three-dimensional digital representations of objects or environments, including mesh generation, surface fitting, and depth estimation from multiple views.

Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.

Integration and processing of data from diverse sensors (e.g., magnetometers, odometers, IMUs, vision sensors) to achieve robust and accurate positioning, especially in environments where GPS is unreliable or unavailable.