Search Results for "segment"

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and...

Mesh R-CNN is a 3D reconstruction and object understanding framework developed by Facebook Research that extends Mask R-CNN into the 3D domain. 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. ...

C++ implementation of the Adaptive and Generic Accelerated Segment Test (AGAST): a highly efficient corner detector based on the same corner test as FAST. For a C implementation please refer to http://sourceforge.net/projects/agast/

Adaptive and Generic Accelerated Segment Test (AGAST): a highly efficient corner detector based on the same corner test as FAST. For a thread-safe C++ implementation please refer to http://sourceforge.net/projects/agastpp/