This talk will summarize our recent works on bridging the gap between natural language and 3D human motions. I will first show results on text-to-motion synthesis, i.e., text-conditioned generative models for controllable motion synthesis, with a special focus on compositionality to handle finegrained textual descriptions. Second, I will present results from our text-to-motion retrieval model. The relevant papers are ACTOR, TEMOS, TMR [Petrovich 2021, 2022, 2023] and TEACH, SINC [Athanasiou 2022, 2023].
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Gül Varol is a permanent researcher in the IMAGINE team at Ecole des Ponts ParisTech. Previously, she was a postdoctoral researcher at the University of Oxford (VGG). She obtained her PhD from the WILLOW team of Inria Paris and Ecole Normale Superieure (ENS). Her thesis received PhD awards from ELLIS and AFRIF. She regularly serves as an Area Chair at major computer vision conferences, and will serve as a Program Chair at ECCV’24. Her research interests cover vision and language applications, including video representation learning, human motion synthesis and sign languages.
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