Simplification and Repair of Polygonal Models Using Volumetric Techniques
By Fakir S. Nooruddin, Greg Turk. 2003
577 citations recorded by the source corpus.
Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Graphics and Computer-Aided Design
- Andrea Tagliasacchi
- Jonathan Richard Shewchuk
- Chen Shen
- Ersin Yumer
- James F. O'Brien
- Ivan Laptev
- Anders P. Eriksson
- Bryan C. Russell
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Jitendra Malik
- Cordelia Schmid
- Dacheng Tao
- Andrew Zisserman
- Ming-Hsuan Yang
- Xiaogang Wang
- Andrea Vedaldi
Citations in the corpus
- Deep Level Sets: Implicit Surface Representations for 3D Shape Inference (2019, methodology): “The IoU is measured by first applying a voxelization procedure [25] to the ground truth as well as the level sets inferred by the trained network.”
- Interpolating and approximating implicit surfaces from polygon soup (2004, methodology): “In these cases, we can pre-process the input to remove polygons that are not visible from the exterior using methods such as those in [Nooruddin and Turk, 2003] and [Nooruddin and Turk, 2000].”
- Robust repair of polygonal models (2004, methodology): “Although other volumetric techniques have been proposed for repairing polygon models [Nooruddin and Turk 2003] or filling holes on the model surface [Curless and Levoy 1996; Davis et al. 2002], our method differs substantially in the following aspects: © 2004 ACM 0730-0301/04/0800-0888 $5.00 1.”
- Implicit Surface Representations As Layers in Neural Networks (2019, methodology): “The ground-truth manifolds are also converted to a voxel occupancy map, for training and testing the voxelbased loss functions, using the procedure of [25].”
- BodyNet: Volumetric Inference of 3D Human Body Shapes (2018, methodology): “We voxelize the ground truth meshes (i.e., SMPL) into a fixed resolution grid using binvox [52,53].”
- 3D Skeletons: A State‐of‐the‐Art Report (2016, methodology): “While analytic methods can be easily converted to image methods by voxelization tools [NT03], the two representations lead to skeletonization methods having quite different properties.”