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Swap the Climber, Keep the Physics Intact
The physical realism of the reference clip stays exactly as it was — only the lead swaps to a student with twin ponytails, like changing a skin, nothing more.
✍️ The real highlight here is that the workflow itself is reusable — convert to a Depth reference first, then swap the lead, no need to redesign the background structure. If you want to save time, just copy this pipeline directly.
📋 Prompt Natural Language
Depth can now reproduce complex climbing and parkour motion cleanly — and this one really holds up.
The method: feed in a fast climbing clip, convert it into a Depth motion reference, then swap the lead for a 20-year-old student with twin ponytails and a backpack, keeping the concrete structure unchanged.
Wall contact, weight transfer, jumps, and the climbing path all stay clean and consistent, full-body motion intact, nothing breaks.
Workflow: ① clip a reference under 15 seconds ② process it with Depth Anything V2 ③ swap the lead to finish the generation. Rendered with GPT-Image 2.
