Research news on Computational 3D vision

Computational 3D vision concerns algorithms and sensor systems that infer three-dimensional structure, motion, and semantics from visual and related signals. Methods span monocular and multi-view 3D reconstruction, depth estimation, inverse rendering, and 4D scene capture, often integrating LiDAR, radar, infrared, and event or neuromorphic sensors. Deep learning architectures and data-driven simulation play central roles in segmentation, pose estimation, anomaly detection, and novel view synthesis, enabling robust perception, mapping, and editing of complex environments for robotics, autonomous systems, and immersive displays.

Robotics

Closing the gap between animal movement and robotic control

Animals move with a level of precision and adaptability that robots struggle to match. In Carnegie Mellon University's Department of Mechanical Engineering, researchers are developing a new AI-driven approach to uncover how ...

Machine learning & AI

AI galaxy hunters could be adding to the global GPU crunch

NASA announced that it will launch the Nancy Grace Roman space telescope into orbit in September 2026, eight months ahead of schedule. The new space telescope is expected to deliver 20,000 terabytes of data to astronomers ...

Engineering

Automated camera solution can improve excavator tracking

Despite significant advances in vision-based equipment tracking, frequent occlusions caused by multiple interacting machines continue to degrade tracking accuracy on construction sites. While previous studies have explored ...

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