This depth-aware, reference-guided video-to-video workflow applies consistent style transfer to your footage while preserving motion and scene geometry. It starts by ingesting your clip with LoadVideo, then computes a per-frame depth map to anchor structure and camera movement (handled by the custom processing node c3b10638-32f0-4101-9b21-21fcda8712d8). The very first frame is extracted and saved (via SaveImage and helper utilities like 8dbec705-cae4-4197-9594-85b48cc18483), then passed to OpenAIGPTImageNodeV2 together with your text prompt from PrimitiveStringMultiline. GPT-Image-2 generates a style-matched reference image from that initial frame, which the workflow uses to steer the overall look.

The core stylization is driven by Seedance 2.0 through ByteDance2ReferenceNode, which fuses three signals: the depth map (structure), the first-frame style reference (appearance), and your prompt (semantic guidance). You can queue up to four style variations in one run using the batch fan-out/collector nodes (a3edb32a-4533-45e3-8eb2-84399225da2e), then reassemble the generated frames into final videos with CreateVideo and SaveVideo. The result is a set of stable, on-style clips that maintain the original timing and motion while reflecting your chosen aesthetic.