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1 Ergebnisse
1
Interaction Transformer for Human Reaction Generation ; We ..:
Chopin, Baptiste
;
Tang, Hao
;
Otberdout, Naima
..
IEEE Transactions on Multimedia. , 2023
Link:
https://hdl.handle.net/20.500.12210/79906
RT Journal T1
Interaction Transformer for Human Reaction Generation ; We address the challenging task of human reaction generation, which aims to generate a corresponding reaction based on an input action. Most of the existing works do not focus on generating and predicting the reaction and cannot generate the motion when only the action is given as input. To address this limitation, we propose a novel interaction Transformer (InterFormer) consisting of a Transformer network with both temporal and spatial attention. Specifically, temporal attention captures the temporal dependencies of the motion of both characters and of their interaction, while spatial attention learns the dependencies between the different body parts of each character and those which are part of the interaction. Moreover, we propose using graphs to increase the performance of spatial attention via an interaction distance module that helps focus on nearby joints from both characters. Extensive experiments on the SBU i...
UL https://suche.suub.uni-bremen.de/peid=base-ftunivlilleoa:oai:lilloa.univ-lille.fr:20.500.12210_79906&Exemplar=1&LAN=DE A1 Chopin, Baptiste A1 Tang, Hao A1 Otberdout, Naima A1 Daoudi, Mohamed A1 Sebe, Nicu PB Institute of Electrical and Electronics Engineers YR 2023 K1 Interaction Transformer Human Reaction Generation;Interaction;Transformer;Human Reaction Generation JF IEEE Transactions on Multimedia LK http://dx.doi.org/https://hdl.handle.net/20.500.12210/79906 DO https://hdl.handle.net/20.500.12210/79906 SF ELIB - SuUB Bremen
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