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This work presents 4DHumanOutfit, a new dataset of densely sampledspatio-temporal 4D human motion data of different actors, outfits and motions.The dataset is designed to contain different actors wearing different outfitswhile performing different motions in each outfit. In this way, the dataset canbe seen as a cube of data containing 4D motion sequences along 3 axes withidentity, outfit and motion. This rich dataset has numerous potentialapplications for the processing and creation of digital humans, e.g. augmentedreality, avatar creation and virtual try on. 4DHumanOutfit is released forresearch purposes at https://kinovis.inria.fr/4dhumanoutfit/. In addition toimage data and 4D reconstructions, the dataset includes reference solutions foreach axis. We present independent baselines along each axis that demonstratethe value of these reference solutions for evaluation tasks.

4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements