Tim Broedermann — accepted AI-conference papers

2025

PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields

Sean Wu, Shamik Basu, Tim Broedermann, Luc Van Gool, Christos Sakaridis

CVPR 2025poster

We tackle the ill-posed inverse rendering problem in 3D reconstruction with a Neural Radiance Field (NeRF) approach informed by Physics-Based Rendering (PBR) theory, named PBR-NeRF. Our method addresses a key limitation in most NeRF and 3D Gaussian Splatting approaches: they estimate view-dependent…

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2023

Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation

David Brüggemann, Christos Sakaridis, Tim Broedermann, Luc Van Gool

ICCV 2023poster

Standard unsupervised domain adaptation methods adapt models from a source to a target domain using labeled source data and unlabeled target data jointly. In model adaptation, on the other hand, access to the labeled source data is prohibited, i.e., only the source-trained model and unlabeled target…

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