0–4s: A hacker wearing a damaged trench coat and a hood covering their face walks down a r | Seedance
0 4s A Hacker Wearing A Damaged Trench is presented as an edited case study, not a copy-ready prompt dump. Use it to study subject framing, camera direction, lighting choices, then rewrite it for your own workflow.
Seedance2Prompt Editorial Team
Reviewed by: Seedance2Prompt Editorial Team
2026-03-12
Prompt detail pages start from approved examples, then the editorial team adds titles, usage notes, and related paths to make them reusable.
0–4s: A hacker wearing a damaged trench coat and a hood covering their face walks down a rainy night street. Neon signs (pink and blue) serve as the main light source, projecting from the upper right of the frame. Rain is visible under the light, hitting the surface of the trench coat. Medium shot, handheld stabilizer following the walk, low angle. Environment: Cyberpunk night market, with steam rising from stalls on both sides. 4–7s: The hacker stops, putting their right hand into the trench coat pocket. The camera slowly pushes in for a close-up. Smoke rises from the stalls behind, illuminated by the neon backlight. 7–15s: The hacker pulls out a holographic device; a blue holographic projection emerges from the device, illuminating the hacker's face. Two drones circle in the background, scanning with red light. The device emits a slight electronic hum upon activation. Camera: Handheld follow → Slow push-in to close-up → Locked close-up Style: anamorphic, grainy, neon saturated tones, low-key lighting Audio: Rain sound ambient bed + distant drone hum + steam hissing + device activation electronic sound (at 3 seconds) Constraints: Maintain stable exposure, no camera drift, character facial continuity, blue light reflection on raindrops
How to work from this case
- Start with the original prompt and identify which subject, camera, and mood phrases drive the output.
- When iterating, change one variable first: lighting, motion, or emotion.
- If references are involved, adjust framing and movement separately for more stable generations.
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Public prompt pages show edited case notes instead of copy-ready raw text. High-risk, explicit, and brand- or likeness-sensitive entries are filtered from the public library.
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