Descriptions:
This tutorial from the Veteran AI channel introduces OneToAllAnimation, a newly released pose-transfer video generation model that its creator claims outperforms Wan Animate in character consistency and artifact reduction. The video’s central demonstration shows how the model applies pose information from a driving video onto a reference image taken from any camera angle — including transitions between half-body and full-body perspectives — without the spatial distortion that commonly appears in competing models.
The walkthrough covers setup inside ComfyUI using Kijai’s Wan Video extension, including model selection between 1.3B and 14B variants and FP8 versus FP16 precision options. Key workflow details include the use of a LightX2V acceleration model with block swapping (set to 32 blocks), a dynamic scheduler, and a two-stage pipeline: a base generation of 81 frames followed by iterative extension segments with 5-frame overlaps that allow videos of theoretically unlimited length. The presenter also demonstrates the workflow running on the Running Hub cloud platform as an alternative to local ComfyUI deployment.
The technical explanation covers how pose and reference image data are injected into the latent space using dedicated embedding nodes — add Wan to all reference embed and add Wan to all pose embed — before sampling. Viewers who want to reproduce the workflow will find practical guidance on model placement, extension installation, and the extension/splicing logic that enables seamless infinite video generation.
📺 Source: Veteran AI · Published December 11, 2025
🏷️ Format: Tutorial Demo
