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SAM4D introduces a 4D foundation model for promptable segmentation across camera and LiDAR streams, addressing the limitations of frame-centric and modality-isolated approaches in autonomous driving. Key Highlights: Paper Resources
You’ve just finished listening to your favorite high-energy workout song on Spotify, and the next track that automatically plays is one you’ve never heard, but it’s a perfect fit for
VideoGameBench is a rigorous benchmark that evaluates VLMs’ real-time decision-making, perception, memory, and planning by challenging them to complete 1990s-era video games with only raw visual inputs and minimal control
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
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
Now you can enjoy this Article in the form of an audio! Imagine an expert sommelier. They don’t just identify a wine; they experience it through multiple senses. They see
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: Paper Resources Related articles
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
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.
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
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
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