Lamp. Hand painted lamp collections
BRIEF
To leverage AI tools in fashion marketing to simulate high-quality photoshoots and pitch-ready imagery without traditional production costs.
The idea stemmed from the need to showcase garments in realistic, styled environments without relying on full-scale shoots. By using generative AI, we aimed to bridge the gap between product photography and lifestyle marketing. The purpose was twofold: to present the clothing in aspirational settings tailored to specific audiences, and to create a repeatable, scalable system for fashion brands to generate visuals that align with their vision.
We started with a flat-lay image of the kurta, training AI models to capture its texture, pattern, silhouette, and drape. We then engineered prompts that layered in audience type, cultural ambience, and environmental context, for an editorial fashion feature. Through iterative refinement, we enhanced realism, lighting, and styling.
Additional AI models were trained, enabling the generation of high-quality editorial visuals across a range of scenarios. This approach allows for quick creation of culturally contextualized marketing imagery, tailored to specific audiences, occasions, or campaign themes, without the logistical load of traditional photoshoots. Designers can visualize collections in different moods, seasons, and settings in a matter of hours. These visuals also serve as valuable assets for social media, digital lookbooks, and e-commerce styling.
We generated a series of fashion editorial aesthetics by combining imaginative visual references with carefully crafted language prompts. These visuals transformed abstract ideas into viable sources of inspiration. Each image captured the essence of the garment, its detailing, ambience, and emotional tone, making them ideal for digital campaigns, magazine features, and e-commerce presentations.
