A survey of point-based techniques in computer graphics

By Leif Kobbelt, Mario Botsch. Computers & graphics, 2004

386 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

View Paper: https://www.semanticscholar.org/paper/1dd4d072dfbd3225e5fb7a36f9c093ff9d6915f8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

In Computer Graphics and Computer-Aided Design

Citations in the corpus

A Surface-Growing Approach to Multi-View Stereo Reconstruction (2007, neutral): “[11, 21]).”
Pix2Shape: Towards Unsupervised Learning of 3D Scenes from Images Using a View-Based Representation (2020, background): “Representing 3D structure as voxels or meshes presents different challenges for generative models (Kobbelt and Botsch 2004).”
SPACE: A Simulator for Physical Interactions and Causal Learning in 3D Environments (2021, background): “But with the advancement and rise of deep learning, computer graphics, and embodied AI [22, 23, 24], there has been a paradigm shift towards generating synthetic datasets that range from simple 2D cartoons [25, 26, 27] to realistic interaction in 3D environments [13, 28, 14, 29, 30, 15], all with th”
Fast and Effective Feature-Preserving Mesh Denoising (2007, background): “Hence, to obtain the same degree of denoising,n is likely to be greater thann1.”
Recent advances in 3D Gaussian splatting (2024, neutral): “For more details about traditional point-based rendering techniques, please refer to [12].”
Accurate, Dense, and Robust Multi-View Stereopsis (2007, background): “Despite the growing popularity of this type of models in the computer graphics community [19], it remains desirable to turn our collection of patches into surface meshes for imagebased modeling applications.”
A Survey on 3D Gaussian Splatting (2024, neutral): “Please see [74, 115, 245, 256, 273] for a comprehensive overview of radiance fields, scene reconstruction and representation, and rendering methods.”
SynSin: End-to-End View Synthesis From a Single Image (2019, background): “Renderers are used extensively in graphics, as reviewed in [29, 49], but they usually focus on forward projection.”
Advances in Neural Rendering (2021, methodology): “In the computer graphics literature, point cloud rendering techniques are extensively used [KB04,SP04].”
A review of algorithms for filtering the 3D point cloud (2017, neutral): “The drawback of MLS is that the process involves a non-linear optimization for finding the reference plane [8].”
Direct visibility of point sets (2007, background): “In the last decade, an alternative to meshes, in the form of a pointbased representation (a point cloud), has gained increasing popularity [Rusinkiewicz and Levoy 2000; Pauly and Gross 2001; Zwicker et al. 2002; Alexa et al. 2003; Fleishman et al. 2003; Alexa et al. 2004; Kobbelt and Botsch 2004].”
Neural Point-Based Graphics (2019, background): “Using points as the modeling primitives for rendering (point-based graphics) was proposed in [9,10] and have been in active development in the 2000s [18,19,11,12].”
Accurate, Dense, and Robust Multiview Stereopsis (2010, background): “Despite the growing popularity of this type of models in the computer graphics community [19], it remains desirable to turn our collection of patches into surface meshes for image-based modeling applications.”