AI Re-dressed Dance Performance in Studio

Three young East Asian women dancing in a minimalist studio. Center woman wears a white ribbed tank top and denim mini skirt; side women wear white crop-top shirts and denim shorts. All in high heels. Background is a grey wall with 'FOCUS ON PROGRESS Not Perfection' text. 0-30s: Synchronized K-pop choreography with hip sways and arm movements. High-definition, studio track lighting.

Modelo

Seedance

Flujo

motion transfer

Duración

30s

Formato

9:16

Cámara

static medium

Estilo

K-pop dance cover, photorealistic

Versión para transferencia de movimiento

Úsalo con un video de referencia y la imagen de tu personaje.

Use the reference video for motion. Keep the exact body motion, timing and camera; replace the performers with three East Asian women in white tops and denim skirts/shorts; setting is a minimalist dance studio with motivational text on the wall.

Prompt negativo

text, watermark, blurry, distorted faces, extra limbs, low resolution

Publicación original

OKAY SO WHILE EVERYONE IS BUILDING CLAUDE + OBSIDIAN SECOND BRAINS — MY AI RE-DRESSING PIPELINE IS QUIETLY PRINTING $16,400 A MONTH Been deep in productivity workflows and local LLM notes lately, but the second machine running in the background is doing all the heavy lifting. Took static photos of real girls, used AI to completely re-dress them, and ran a motion-transfer script to make them dance in 4K sync. Sounds like a gimmick until you check the Stripe dashboard. $500 in GPU compute. $16,400 out. Two months. Subscriptions, clothing brand promos, and custom video requests — all stacking on top of each other while people spend 4 hours tweaking note-taking apps. The wild part? Dancing is just 1% of this. Once you master the photo-to-video re-dressing pipeline, you can put these models in any outfit, any location, doing literally anything. Infinite content leverage off a single PC setup. Curious if you want the step-by-step breakdown of this image-to-video workflow, or should I stick to Obsidian setups? Drop a comment below.