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Titel: Synthesis of Compositional Animations from Textual Descriptions
VerfasserIn: Ghosh, Anindita
Cheema, Noshaba
Oguz, Cennet
Theobalt, Christian
Slusallek, Philipp
Sprache: Englisch
Verlag/Plattform: arXiv
Erscheinungsjahr: 2021
DDC-Sachgruppe: 004 Informatik
Dokumenttyp: Sonstiges
Abstract: "How can we animate 3D-characters from a movie script or move robots by simply telling them what we would like them to do?" "How unstructured and complex can we make a sentence and still generate plausible movements from it?" These are questions that need to be answered in the long-run, as the field is still in its infancy. Inspired by these problems, we present a new technique for generating compositional actions, which handles complex input sentences. Our output is a 3D pose sequence depicting the actions in the input sentence. We propose a hierarchical two-stream sequential model to explore a finer joint-level mapping between natural language sentences and 3D pose sequences corresponding to the given motion. We learn two manifold representations of the motion -- one each for the upper body and the lower body movements. Our model can generate plausible pose sequences for short sentences describing single actions as well as long compositional sentences describing multiple sequential and superimposed actions. We evaluate our proposed model on the publicly available KIT Motion-Language Dataset containing 3D pose data with human-annotated sentences. Experimental results show that our model advances the state-of-the-art on text-based motion synthesis in objective evaluations by a margin of 50%. Qualitative evaluations based on a user study indicate that our synthesized motions are perceived to be the closest to the ground-truth motion captures for both short and compositional sentences.
DOI der Erstveröffentlichung: 10.48550/arXiv.2103.14675
URL der Erstveröffentlichung: https://arxiv.org/abs/2103.14675
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-391773
hdl:20.500.11880/35321
http://dx.doi.org/10.22028/D291-39177
Datum des Eintrags: 28-Feb-2023
Bemerkung/Hinweis: Preprint
Fakultät: MI - Fakultät für Mathematik und Informatik
Fachrichtung: MI - Informatik
Professur: MI - Prof. Dr. Philipp Slusallek
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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