Technology Transfer Project
Text4Pose: Leveraging text to improve human pose, shape, motion estimation and generation
Type
Technology Transfer Contract
Start Date
15/09/2021
End Date
15/09/2024
Staff
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Delmas, Ginger Diana
Member
Project Description
The goal of the project is to study how text information can be leveraged in order to improve problems related to human pose: estimating human pose and shape in images or in videos, as well as predicting future human motion.
This project is a collaboration between IRI and Naver Labs Europe.
Project Publications
Journal Publications
Conference Publications
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G.D. Delmas, P. Weinzaepfel, F. Moreno-Noguer and G. Rogez. PoseEmbroider: towards a 3D, visual, semantic-aware human pose representation, 18th European Conference on Computer Vision, 2024, Milano, Italy, in Computer Vision – ECCV 2024, Vol 15110 of Lecture Notes in Computer Science, pp. 55-73, 2024.
Abstract
Info
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G.D. Delmas, P. Weinzaepfel, F. Moreno-Noguer and G. Rogez. PoseFix: correcting 3D human poses with natural language, 2023 International Conference on Computer Vision, 2023, Paris, France, pp. 14972-14982.
Abstract
Info
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G.D. Delmas, P. Weinzaepfel, T. Lucas, F. Moreno-Noguer and G. Rogez. PoseScript: 3D human poses from natural language, 17th European Conference on Computer Vision, 2022, Tel Aviv (Israel), in Computer Vision – ECCV 2022 , Vol 13666 of Lecture Notes in Computer Science, pp. 346-362, 2022.
Abstract
Info
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