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[{argument name="car brand name"default="CAR_BRAND"}] 브랜드의 정확한 공식 서체를 사용하여 제작된, 매우 사실적이고 고품질의 3D 렌더링 이미지입니다. 이 이미지는 [{argument name="car brand name"default="CAR_BRAND"}]의 유산, 엔지니어링 정신, 문화적 정체성을 진정성 있게 반영하는 상징적인 환경에 완벽하게 통합되어 있습니다. 장면 중앙에는 [{argument name="car brand name"default="CAR_BRAND"}]의 포토리얼리스틱하고 실제 생산 차량과 동일한 차량이 배치되어 있으며, 배지, 그릴, 휠 디자인까지 즉시 알아볼 수 있도록 세밀하게 묘사되어 있습니다. 자연광, 정확한 기상 조건, 물리 기반 재료를 사용하여 현실에 기반을 둔 배경을 연출했습니다. 오른쪽 상단에는 [{argument name="car brand name"default="CAR_BRAND"}]의 공식 로고가 미묘한 투명도와 함께 깔끔하게 오버레이되어 있습니다. 시네마틱 피사계 심도, 레이 트레이싱 반사, 전문 자동차 사진과 구별할 수 없는 스튜디오급 사실감으로 렌더링되었습니다.
제품 마케팅 - 초현실적인 3D 자동차 브랜드 렌더링
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자동차 브랜드의 이름과 로고를 사실적이고 생산에 적합한 차량과 통합하여 초현실적이고 고품질의 3D 렌더링을 생성하도록 설계된 프롬프트입니다. 전문적인 자동차 사진 촬영에 적합하도록 브랜드의 유산과 엔지니어링 정신을 반영하는 영화 같은 품질, 레이 트레이싱 반사 및 세심한 디테일을 강조합니다.
A highly detailed JSON prompt for generating hyper-realistic automotive lifestyle photography during the golden hour. The scene features a professional model with a toned physique washing a {argument name="car type" default="Lamborghini Aventador"} (implied by context/image) in a luxury setting. The prompt specifies dramatic backlighting, intense specular highlights on the wet surface, and a sensual, glamorous mood.
A detailed JSON prompt for an ultra-photorealistic image of a young woman resembling Amanda Seyfried in Y2K streetwear (graphic crop top, distressed micro-shorts, studded belt). The scene is set at dusk by a vibrant orange sports car on a coastal road, emphasizing cinematic lighting, high contrast, and ray tracing reflections.
A detailed JSON prompt for generating an ultra-realistic, cinematic automotive portrait. It requires strict identity preservation of the female subject from a reference image, posing with a black Mahindra Thar Roxx in a dim basement garage, using an overhead high-angle shot and soft sunbeam lighting.
A detailed JSON prompt for generating an ultra-realistic, cinematic automotive portrait. It requires strict identity preservation of the female subject from a reference image, posing with a black Mahindra Thar Roxx in a dim basement garage, using an overhead high-angle shot and soft sunbeam lighting.
A structured JSON prompt for Nano Banana Pro to generate an 8K, photorealistic automotive fashion portrait. The subject is a young woman sitting on asphalt, leaning against the bumper of a matte metallic red-orange supercar, detailing her attire (black corset, thigh-high boots) and the technical style (eye-level, shallow depth of field).
A highly detailed, structured prompt designed to transform an uploaded image into a hyperrealistic, cinematic triptych-style portrait focused on a modern urban automotive lifestyle scene, emphasizing high resolution and professional photography techniques.
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TCF vendors
Exponential Interactive, Inc d/b/a VDX.tv
Cookie duration: 90 (days).
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Authentication-derived identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Non-precise location data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
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