Antonio Oroz — accepted AI-conference papers

2026

PercHead: Perceptual Head Model for Single-Image 3D Head Reconstruction & Editing

Antonio Oroz, Matthias Nießner, Tobias Kirschstein

CVPR 2026

We present PercHead, a model for single-image 3D head reconstruction and disentangled 3D editing - two tasks that are inherently challenging due to ambiguity in plausible explanations for the same input. At the heart of our approach lies our novel perceptual loss based on DINOv2 and SAM 2.1. Unlike

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2024

Uncertainty for Active Learning on Graphs

Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier, Antonio Oroz, Stephan Günnemann

ICML 2024poster

Uncertainty Sampling is an Active Learning strategy that aims to improve the data efficiency of machine learning models by iteratively acquiring labels of data points with the highest uncertainty. While it has proven effective for independent data its applicability to graphs remains under-explored.…

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