An algorithm and data structure for 3D object synthesis using surface patch intersections

By Wayne E. Carlson. 1982

Subfields: 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 Vision and Pattern Recognition

1. Song-Chun Zhu
2. Luc Van Gool
3. Jitendra Malik
4. Andrea Vedaldi
5. Ming-Hsuan Yang
6. Josh Tenenbaum
7. Dacheng Tao
8. Andrew Zisserman

Citations in the corpus

• Learning Descriptor Networks for 3D Shape Synthesis and Analysis (2018, background): “Researchers in the fields of graphics and vision have studied the 3D object synthesis problems [2, 3, 9].”
• Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016, background): “…3D object understanding and generation is an important problem in the graphics and vision community, and the relevant literature is very rich [Carlson, 1982, Tangelder and Veltkamp, 2008, Van Kaick et al., 2011, Blanz and Vetter, 1999, Kalogerakis et al., 2012, Chaudhuri et al., 2011, Xue et…”
• SurfNet: Generating 3D Shape Surfaces Using Deep Residual Networks (2017, background): “Early works focussed on coherent synthesis of 3D primitives and surface patches [3].”