B Jiang, X Chen, W Liu, J Yu, G Yu… - Advances in Neural …, 2023 - proceedings.neurips.cc
Though the advancement of pre-trained large language models unfolds, the exploration of building a unified model for language and other multimodal data, such as motion, remains …
S Xu, Z Li, YX Wang, LY Gui - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most existing research on HOI synthesis lacks comprehensive whole-body interactions with …
Abstract 3D human motion generation is crucial for creative industry. Recent advances rely on generative models with domain knowledge for text-driven motion generation, leading to …
In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset. Existing motion datasets predominantly contain body-only poses, lacking facial expressions …
We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts. Directly learning a conditional …
H Liang, W Zhang, W Li, J Yu, L Xu - International Journal of Computer …, 2024 - Springer
We have recently seen tremendous progress in diffusion advances for generating realistic human motions. Yet, they largely disregard the multi-human interactions. In this paper, we …
In this paper, we present TMR, a simple yet effective approach for text to 3D human motion retrieval. While previous work has only treated retrieval as a proxy evaluation metric, we …
P Jin, Y Wu, Y Fan, Z Sun, W Yang… - Advances in Neural …, 2024 - proceedings.neurips.cc
Most text-driven human motion generation methods employ sequential modeling approaches, eg, transformer, to extract sentence-level text representations automatically and …
Our goal is to synthesize 3D human motions given textual inputs describing simultaneous actions, for examplewaving hand'whilewalking'at the same time. We refer to generating such …