Difference between revisions of "Google Summer of Code/2024"
From BRL-CAD
(Added GSoC 2024 info) |
(→Neural rendering) |
||
| (2 intermediate revisions by 2 users not shown) | |||
| Line 20: | Line 20: | ||
--> | --> | ||
| + | |||
| + | == Neural rendering == | ||
| + | * Description: The project aims to explore the feasibility of using neural networks to accelerate ray tracing for 3D rendering, investigating whether neural nets can be leveraged for arbitrary shot line queries more accurately and efficiently than direct computation. | ||
| + | * Org: BRL-CAD | ||
| + | * Student: [[User:Bralani]] | ||
| + | * [[User:Bralani/GSoC2024/Abstract|Abstract]] | ||
| + | * [[https://drive.google.com/file/d/1UBOlF0EpeF7-3MySNlIC2VsgJt6Na-rn/view?usp=sharing|Project Plan]] | ||
| + | * [[User:Bralani/GSoC2024/Log|Dev Log]] | ||
| + | |||
| + | == Neural rendering == | ||
| + | * Description: The project aims to explore the feasibility of using neural networks to accelerate ray tracing for 3D rendering, investigating whether neural nets can be leveraged for arbitrary shot line queries more accurately and efficiently than direct computation. | ||
| + | * Org: BRL-CAD | ||
| + | * Student: [[User:Jin Ke| Jin Ke]] | ||
| + | * [https://drive.google.com/file/d/12YM3_aXDnFhSo3UilPz1ImUy1P6xmmGZ/view?usp=sharing Project Plan] | ||
| + | * [[User:Jin_Ke|Dev Log]] | ||
Latest revision as of 10:54, 6 July 2024
GSoC 2024 With BRL-CAD[edit]
BRL-CAD was accepted as an umbrella mentoring organization for the Google Summer of Code! This year, we accepted 9 students to work on IfcOpenShell, BRL-CAD, KiCad, Appleseed, Manifold and OpenSCAD.
Accepted Projects[edit]
Neural rendering[edit]
- Description: The project aims to explore the feasibility of using neural networks to accelerate ray tracing for 3D rendering, investigating whether neural nets can be leveraged for arbitrary shot line queries more accurately and efficiently than direct computation.
- Org: BRL-CAD
- Student: User:Bralani
- Abstract
- [Plan]
- Dev Log
Neural rendering[edit]
- Description: The project aims to explore the feasibility of using neural networks to accelerate ray tracing for 3D rendering, investigating whether neural nets can be leveraged for arbitrary shot line queries more accurately and efficiently than direct computation.
- Org: BRL-CAD
- Student: Jin Ke
- Project Plan
- Dev Log
