We study the challenge of sign language video mimicking: given a driving video and a single reference frame, synthesize a video where the target signer reproduces the source motion while preserving identity and linguistic form. Prior pipelines entangle rigid motion, non-rigid deformation, and view-dependent completion...
Zhe-Wen He, Jun-Yi Yu, Hao Huang et al.· 0 citations
SignDino, a self-supervised sign-video encoder that moves the DINOv3 student--teacher recipe from the spatial domain of image crops to the temporal domain of tracked sign streams, provides a strong public self-supervised representation and shows competitive or state-of-the-art performance under matched downstream evalu...
Jun-Yi Hu, Zhe-Wen He, Hao Huang et al.· 0 citations
VTaMo is presented, a framework that introduces explicit multi-granularity alignment at three levels: local alignment via entropy-regularized optimal transport with a learnable null token for fine-grained frame-to-token correspondences; global alignment via a learnable orthogonal transformation that calibrates embeddin...