DreamActor V2
DreamActor V2 is a video generation model developed by ByteDance that animates static images by transferring motion from a reference driving video onto a target character. It is the second generation of ByteDance's DreamActor series and was made available in February 2026. Rather than relying on skeleton extraction or pose estimation pipelines, it uses a spatiotemporal in-context learning framework that reads motion directly from raw video pixels, which allows it to handle character types that traditional pose-based methods struggle with, including animals, cartoon mascots, fantasy creatures, and 3D renders.