Cedric Perauer

Hello, I’m Cedric. I am interested in scene understanding and generation. I am currently working as Computer Vision/ML Engineer at Hexagon. Previously, I was a Master’s student at TUM and did my thesis with Dr. Alexey Artemov at the TUM Visual Computing & AI Lab. I also worked on Computer Vision for Robotics at Apple , automated driving at Bosch and Mercedes and was a computer vision engineer at CombatIQ. I am passionate about bringing the latest research into products and working on the full stack from outcome driven research to runtime optimization/deployment of models. I enjoy reimplenting papers and following the latest research.

Selected Publications

AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D Scans

Cedric Perauer, Laurenz Adrian Heidrich, Haifan Zhang, Matthias Nießner, Anastasiia Kornilova^*, and Alexey Artemov^*

In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024

arXiv Project Page Code

Selected Projects

Latent Generative Anamorphoses

2D latent generative anamorphoses with Stable Diffusion 3.5, inspired by LookingGlass (CVPR2025)

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Training-Free 360° Panorama Generation

Progressive inpainting via equirectangular projection based on Meta's 2025 ICCV paper "A recipe for generating 3D worlds from a single image"

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Nvidia SANA Inpainting

Inpainting implementation for Nvidia SANA [ICLR2025] using masked Flow scheduler

Project Page Code

Selected Patents

Method and device for recognizing a parking space for a vehicle using machine learning

DE102022205910A1 December 2023

We propose a novel backbone agnostic neural network head that builds on the geometrical characteristics of parking spaces.

Process for camera-based environment detection

DE102021002798A1 July 2021

Our method proposes the use of Neural Rendering (NeRF) for environment perception in the ADAS space.