Author

Lars Doorenbos

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Preprint Sep 2026

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

A novel self-supervised approach that leverages generative uncertainty from text-to-video (T2V) diffusion models to learn semantic similarity without human annotations to identify stable semantic features within existing pretrained representations, such as VideoMAE and V-JEPA.

Enrico Pallotta, Sina Raoufi, Lars Doorenbos et al. · 0 citations

Preprint Aug 2026

Multi-Person Human Motion Forecasting in Complex Scenes

Object-Conditioned Social Diffusion is proposed, a conditional diffusion model that integrates motion history, multi-person interactions, and object cues into a single framework that reduces the two-second path error, produces more realistic long-term forecasts, and supports sampling multiple plausible futures.

Serdar Ozsoy, Lars Doorenbos, Juergen Gall · 0 citations

#machine learning Preprint Aug 2026

Post-Training VLMs for Video Mistake Detection

This work proposes the first video-language-model post-training technique for mistake detection, which uses a tailored reward function to encourage the model to identify discrepancies between an instruction and the corresponding video, and generalizes especially well to unseen procedures.

Federico Spurio, Olga Zatsarynna, Lars Doorenbos et al. · 1 citation