NIST's neural network model captured 97% of objects in a defined set of test images, locating the objects' centers to within a few pixels of manually selected locations.

The accurate detection of small object in optical remote sensing images (ORSIs) presents a significant challenge due to the background interference and the small size of the objects, making them ...

In recent times deep neural networks have become very successful in solving traditionally hard problems in Computer Vision such as Object Detection. This is due to their ability to find hidden ...

Segment Anything, recently released by Facebook Research, does something that most people who have dabbled in computer vision have found daunting: reliably figure out which pixels in an image belon… ...

StoryKit is a set of web-based tools, built by BBC R&D to enable the production of Object-Based or Flexible Media experiences without the need to write bespoke code. The aim being to work with ...

Researchers at the Indian Institute of Science (IISc) have pioneered a solution for AI training in Mixed Reality (MR) industrial applications. Overcoming the challenge of extensive image dataset ...

Meta's image segmentation model could have a lot of applications, including in AR and VR. Meta's new AI model can identify objects in images. Here's why that matters | ZDNET ...

The model can create objects with "high-fidelity textures and complex geometric details," NVIDIA's Isha Salian wrote in a blog post.The shapes GET3D makes "are in the form of a triangle mesh, like ...