Author

Tim Engelbracht

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#machine learning Jul 2026

LIME: Learning Intent-aware Camera Motion from Egocentric Video

LIME is proposed, a vision-language camera-motion generator that combines an autoregressive observation-gain output with a continuous flow-matching pose head that learns intent-conditioned camera motion from passive egocentric video, turning ordinary human recordings into supervision for a reusable active-perception pr...

Bo-Yang Sun, Jiajie Li, Yung-Hsu Yang et al. · arXiv.org · 3 citations

#artificial intelligence Feb 2026

Articulated 3D Scene Graphs for Open-World Mobile Manipulation

MoMa-SG, a novel framework for building semantic-kinematic 3D scene graphs of articulated scenes containing a myriad of interactable objects, and the Arti4D-Semantic dataset, which provides parent-child relation annotations between container and contained objects together with object axis annotations across 62 in-the-w...

Martin Buchner, Adrian Rofer, Tim Engelbracht et al. · arXiv.org · 12 citations

#artificial intelligence Preprint Sep 2026

ForceTwin: Physics-informed Digital Twins for Robotic Manipulation from Instrumented Human Interaction

ForceTwin is a system for identifying physics-informed digital twins of articulated objects from instrumented human interaction that achieves 87% goal completion across nine object-embodiment pairs, compared with 60% using VLM-prior and 57% using kinematics-only twins.

Tim Engelbracht, René Zurbrügg, Mayank Mittal et al. · 0 citations