3 papers indexed
Yifei Zhu, Mingyi Shi, Yangyang Cai, Miao Cheng, Yoshifumi Kitamura, Taku Komura
Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to first project motion data into a structured semantic space and then train a generative model within that space. Such a paradigm ha…
Dafei Qin, Rui Xu, Zeyu Shen, Kaichun Qiao, Hongyang Lin, Qixuan Zhang, et al.
Generative CAD modeling has broad design and application potential. Despite significant advances in Boundary Representation (B-Rep) generation, the dominant representation in CAD, existing methods largely depend on uniformly sampled point- or grid-based geometry representations,…
Mingyi Shi, Xuelin Chen, Taku Komura
Synthesizing hand motion that matches the full body motion and the semantic labels is a difficult task due to their high degrees of freedom and the lack of semantic labels. To cope with this issue, we propose a prior-first, condition-second framework for body-conditioned hand mot…