Vorch-Human is presented, a unified human-centric generation framework built on a dual-stream audio-video diffusion transformer that augments the conventional noisy audio/noisy video interface with clean condition-audio and condition-video token groups and adapts to long-form audio-driven generation by training with cl...
Vorch-Omni is presented, a unified multi-task framework for audio-visual synthesis based on an arbitrary-condition-to-arbitrary-output formulation that supports over 10 tasks, including text-to-video, text-to-audio-video, image- and reference-conditioned generation, temporal extension, audio-driven generation, video tr...
Vorch Team, Xiaoyu Chen, Yang Ding et al.· 0 citations
Vorch-Director is proposed, a noise-level-aware residual correction strategy that associates each residual with its originating noise level and injects residuals from matched noise regimes during training to produce more realistic autoregressive histories while retaining efficient teacher-forcing training.
Vorch-IR is presented, a unified framework that supports single- and dual-person identity replacement, with optional background replacement, in a single model, and an automatic data construction pipeline that synthesizes paired supervision for all four editing settings is developed.
Yao-Wei Wang, Xiaoyu Chen, Xin Ma et al.· 0 citations
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