Abstract: This paper presents a detailed review of recent advancements in 3D indoor scene segmentation driven by deep learning techniques. It provides an overview of existing segmentation models, ...

Is your feature request related to a problem? Please describe. Current MONAI segmentation metrics aggregate scores globally. In multi-instance medical segmentation tasks this can mask clinically ...

Watch as an artist transforms a simple canvas into a stunning textured wave painting using modeling paste and acrylic paints. This step-by-step demonstration covers every aspect, from sketching the ...

Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT data). In ...

Medical image segmentation is a fundamental component of many clinical applications such as computer-aided diagnosis, radiotherapy planning, and preoperative planning. Its accuracy and stability ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

I’m training a pre-trained maisi-rflow model to generate new images conditioned on segmentation masks generated with vista3D. In MAISI-data is written that the pseudo-labels can be produced using ...

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...

Have you ever imagined turning your ideas into physical objects with just a few clicks? Thanks to tools like Tinkercad, what once seemed like science fiction is now an accessible reality for anyone ...