Towards Robust 3D Pose Transfer with Adversarial Learning

arXiv:2404.02242v1 Announce Type: new
Abstract: 3D pose transfer that aims to transfer the desired pose to a target mesh is one of the most challenging 3D generation tasks. Previous attempts rely on well-defined parametric human models or skeletal joints as driving pose sources. However, to obtain those clean pose sources, cumbersome but necessary pre-processing pipelines are inevitable, hindering implementations of the real-time applications. This work is driven by the intuition that the robustness of the model can be enhanced by …

abstract adversarial adversarial learning arxiv cs.cv driving however human mesh parametric robust tasks transfer type