Search Results for "gap"

...Built on top of Detectron2 and PyTorch3D, Mesh R-CNN enables end-to-end 3D mesh prediction directly from single RGB images. The model learns to detect, segment, and reconstruct detailed 3D mesh representations of objects in natural images, bridging the gap between 2D perception and 3D understanding. Unlike voxel-based or point-based approaches, Mesh R-CNN uses a differentiable mesh representation, allowing it to efficiently refine surface geometry while maintaining high spatial detail. The system combines 2D detection from Mask R-CNN with 3D reasoning modules that output full mesh reconstructions aligned with the input image. ...

...Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within neural networks to train models to perform image transformations, epipolar geometry, depth estimation, and low-level image processing such as filtering and edge detection that operate directly on tensors. With Kornia we fill the gap between classical and deep computer vision that implements standard and advanced vision algorithms for AI. Our libraries and initiatives are always according to the community needs.

...Usually many operations in 3D workflow are highly redundant and often actions have to be repeated several times or instead being executed in self-made scripts.Scripting is in fact for most people a very nasty and time consuming action. This application module tries to fill the gap where it learns workflows which can in order be modified, multiplied, adapted organically to allow a fast and versatile Workflows, where currently rigid working habits will not Compete. ...also making scripting finally obsolete. currently the development is started with Autodesk Maya. More 3D platforms will come after this project is succeeding.