With Style2Fab, makers can rapidly customize models of 3D-printable objects, such as assistive devices, without hampering their functionality.

The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.

Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.

By synchronizing media streams transmitted from the cloud to two devices, researchers could improve cloud gaming and AR/VR applications.

Produced with techniques borrowed from Japanese paper-cutting, the strong metal lattices are lighter than cork and have customizable mechanical properties.

Developed by MIT researchers, BrightMarkers are invisible fluorescent tags embedded in physical objects to enhance motion tracking, virtual reality, and object detection.

Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.

A new computer vision system turns any shiny object into a camera of sorts, enabling an observer to see around corners or beyond obstructions.