Abstract:

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].

Bio: Gül Varol is a permanent researcher in the IMAGINE team at École 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 École Normale Supérieure (ENS). Her thesis received the PhD awards from ELLIS and AFRIF. Her research is focused on computer vision, specifically video representation learning, human motion analysis, and sign languages.

Organizer: Hossein Azizpour