Lukas Radl

I'm a University Project Assistant/PhD Student at the Institute of Computer Graphics and Vision, Graz University of Technology, where I mostly work on 3D Scene Representations, supervised by Markus Steinberger.

Previously, I received my Master's degree in Computer Science (with distinction) and my Bachelor's degree in Software Engineering both at Graz University of Technology between 2018 and 2023. During this time, I worked as a study assistant, supporting various visual computing classes. In 2019 & 2020, I was featured on the Dean's List of my faculty.

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News

Research

I'm interested in computer graphics, computer vision, machine learning and parallel processing. Most of my work focuses on editable, view-consistent 3D scene representations.

Frustum Volume Caching for Accelerated NeRF Rendering
Michael Steiner, Thomas Köhler, Lukas Radl, Markus Steinberger.
PACMCGIT, 2024.

We leverage the architecture of Instant-NGP to cache view-independent latent codes in a frustum voxel grid for high-quality real-time and offline rendering.

StopThePop: Sorted Gaussian Splatting for View-Consistent Real-time Rendering
Lukas Radl*, Michael Steiner*, Mathias Parger, Alexander Weinrauch, Bernhard Kerbl, Markus Steinberger.
SIGGRAPH, 2024.

Sorting 3D Gaussians along view rays leads to increased view-consistency. With our hierarchical, GPU-friendly resorting scheme, our renderer is only 4% slower than 3DGS on average.

LAENeRF: Local Appearance Editing for Neural Radiance Fields
Lukas Radl, Michael Steiner, Andreas Kurz, Markus Steinberger.
CVPR, 2024.

Locally Stylized Neural Radiance Fields via point-based 3D style transfer with geometry-aware losses - reduced background artefacts, more detail retention and view-consistency.

Analyzing the Internals of Neural Radiance Fields
Lukas Radl, Andreas Kurz, Michael Steiner, Markus Steinberger.
CVPR Workshop on Neural Rendering Intelligence, 2024.

Using density estimates derived from activations for inverse transform sampling in NeRFs allows for faster inference and comparable visual quality.

clean-usnob AVT: Multicenter aortic vessel tree CTA dataset collection with ground truth segmentation masks
Lukas Radl, Yuan Jin, Antonio Pepe, Jianning Li, Christina Gsaxner, Fen-hua Zhao, Jan Egger.
Data in Brief (40), 2022.

Method and apparatus for aorta segmentation in Slicer3D, as well as an open-source CTA dataset with ground-truth annotations, to be used in research.

Reviewing

Starting 2024, I have been reviewing for several journals and conferences!

  • Computers & Graphics
  • Computer Graphics Forum (CGF)

Teaching

I have been involved in teaching for various visual computing courses: ☀️ denotes a course in the summer term, ❄️ denotes a course in the winter term.

Tutoring

Study Assistant work: Supporting students during the exercise, grading and interviews.

2022/23

  • Real-Time Graphics: Exercise ❄️
  • Mathematical Principles in Visual Computing: Exercise ☀️
  • Computergraphics: Exercise ☀️
  • Computer Vision: Exercise ☀️

2021/22

  • Real-Time Graphics: Exercise ❄️
  • Computergraphics: Exercise ☀️
  • Computer Vision: Exercise ☀️

2020/21

  • Computergraphics: Exercise ☀️
  • Computer Vision: Exercise ☀️

Exercise Coordination

Since starting my PhD, I'm now coordinating exercises for visual computing courses.

2024/25

  • Real-Time Graphics: Exercise ❄️
  • Object-Oriented Programming 1: Exercise ❄️
  • Writing Scientific Papers: Seminar ❄️
  • Computergraphics: Exercise ☀️

2023/24

  • Real-Time Graphics: Exercise ❄️
  • Computergraphics: Exercise ☀️

Open Student Projects!

We are interested in real-time rendering in general, with a specific focus on Radiance Fields.

clean-usnob Currently Open Projects!

Advancing 3D Gaussian Splatting
StopThePop in gsplat
Real-Time Rendering of Gaussian Splats with Vulkan

If you're interested in any open student projects, contact me (preferably via E-Mail)!

Template adapted from Jon Barron.