Page 13: 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.

Consumer & Gadgets

AI tech breathes life into virtual companion animals

Researchers at UNIST have developed an innovative AI technology capable of reconstructing highly detailed three-dimensional (3D) models of companion animals from a single photograph, enabling realistic animations. This breakthrough ...

Machine learning & AI

AI model uncovers and reconstructs hidden multi-entity relationships

Just like when multiple people gather simultaneously in a meeting room, higher-order interactions—where many entities interact at once—occur across various fields and reflect the complexity of real-world relationships. However, ...

Computer Sciences

New AI tool learns to read medical images with far less data

A new artificial intelligence (AI) tool could make it much easier—and cheaper—for doctors and researchers to train medical imaging software, even when only a small number of patient scans are available.

Machine learning & AI

Researchers optimize AI systems for science

Using services like ChatGPT or Microsoft Copilot can sometimes seem like magic—to the point it can be easy to forget about the advanced science running behind the scenes of any artificial intelligence (AI) system. Like any ...

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