
90s Retro Streetwear Fashion Editorial
A cinematic fashion editorial prompt that captures a group of diverse young adults in 90s-inspired streetwear around an urban newsstand, featuring dynamic motion and soft cinematic lighting.
This is a gpt-image-2 prompt case for 时尚美妆. Use the copy-ready prompt below to generate similar visuals, and review YouMind OpenLab awesome-gpt-image-2 attribution plus commercial-use rights before reuse.
Prompt
Copy-ready prompt
A cinematic, high-fashion scene.{argument name="group of people" default="8 young people from diverse backgrounds"} A group gathers around a retro urban newsstand, its prominent "NEWSSTAND" sign prominently displayed. The scene is set in a rugged indoor street environment, with worn concrete floors, dark industrial walls, and subtle urban details. Newspapers flutter dynamically in the air, creating a layered sense of depth and a vibrant, natural motion blur. The characters are dressed in carefully coordinated 90s retro streetwear—oversized jackets, layered looks, sunglasses, baseball caps, and understated {argument name="color palette" default="Earth tones (olive green, brown, beige, navy blue)"} The composition is well-balanced: one model casually leans against a newsstand holding a newspaper, another sits confidently on a beige vintage scooter in the foreground, another leans against a cyan scooter, and the rest stand or sit in relaxed, confident poses, their expressions composed.{argument name="camera angle" default="A slightly overhead view (God's-eye view)"} Shot using a 35mm wide-angle lens to maintain natural proportions. The lighting and shadows create a soft, cinematic feel, with warm highlights and soft shadows, evoking a high-end fashion editorial atmosphere. The background includes scattered newspapers, a red fire hydrant, and industrial textures, enhancing realism. Ultra-high detail, photorealistic quality, shallow depth of field, sharp subject focus, smooth film grain, natural color gradation, high-end magazine aesthetics, and 4K resolution.Prompt variables
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