OpenCV and sponsors at Intrinsic, BOP, and University of Hawaiʻi at Mānoa are excited to announce the prize winners of the first Perception Challenge for Bin-Picking, first revealed at CVPR during the Perception for Industrial Robotics workshop. Beginning in February 2025, this challenge had over $60,000 at stake and over 450 teams vying for a…
LeGO-LOAM introduces a cutting-edge lidar odometry and mapping framework designed to deliver real-time, accurate 6-DOF pose estimation for ground vehicles, optimized for challenging, variable terrain environments. It significantly reduces computational overhead while maintaining high accuracy, making it ideal for embedded systems. Key Highlights Ground-Optimized Approach – Segments lidar point clouds by leveraging ground plane information, filtering…
Imagine machines that don’t just capture pixels but truly understand them, recognizing objects, reading text, interpreting scenes, and even “speaking” about images as fluently as a human. VLMs merge computer vision’s “sight” with language’s “speech,” letting AI both describe and converse about any picture it sees. From generating captions and answering questions to counting objects,…
Imagine an expert sommelier. They don’t just identify a wine; they experience it through multiple senses. They see its deep ruby color, inhale its bouquet of black cherry and oak, and taste its complex notes on their palate. They then translate this rich, sensory experience into evocative language, describing it as a “bold Cabernet Sauvignon…
Reliable-loc introduces a resilient LiDAR-based global localization system for wearable mapping devices in complex, GNSS-denied street environments with sparse features and incomplete prior maps. Key Highlights: Dual-Stage Observation Model for MCL: Fuses global and local features into Monte Carlo Localization (MCL), using spectral matching and pose error metrics to refine particle weights in feature-poor scenes.…
Ever heard of an AI cracking a coding bug that stumped a 30-year C++ FAANG veteran for four years and 200 hours of debugging? That just happened. The hero? Anthropic’s newly unveiled Claude 4. This isn’t just a cool story; it’s a preview of the serious firepower Anthropic is unleashing today with Claude Opus 4…
In the ever-evolving world of artificial intelligence, breakthroughs don’t always mean bigger models; they often mean smarter, more efficient architectures. Microsoft’s Phi-4 series is a perfect illustration of this principle. By harnessing advanced training techniques and high-quality curated data, Microsoft has engineered a family of small language models that excel at complex reasoning tasks, yet…
This is the world’s first SLAM dataset recorded onboard real roller coasters, offering extreme motion dynamics, perceptual challenges, and unique conditions for benchmarking SLAM algorithms under aggressive real-world trajectories. Key Highlights: Unprecedented Motion Dynamics – Captures high-acceleration motion with rapid velocity changes, sharp turns, and steep vertical drops, providing a stress test for visual-inertial odometry and…
The convenience of clicking “buy now” or instantly transferring funds has become second nature. But beneath this seamless digital surface lurks a rapidly growing shadow: online transaction fraud. This isn’t just a minor nuisance; it’s a global crisis. In 2024 alone, consumers reported staggering losses exceeding $12.5 billion due to fraud, a 25% jump from…
This paper introduces a SLAM framework that achieves real-time CPU-only performance in dense, registration-error-minimization-based odometry and mapping by leveraging exact point cloud downsampling via coreset extraction, eliminating the need for GPU acceleration. Key Highlights Exact Point Cloud Downsampling via Coresets – Selects a minimal subset of residuals that exactly preserve the quadratic registration error function for a given pose,…