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Completed Project
StyleForge: Fashion Synthesis Through Adversarial Networks
Generative adversarial networks exploration for automated high-fidelity fashion generation and multi-modal style synthesis.
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RoleAuthor & AI Researcher
Timeline2024
TeamResearch Project
Tech Stack5 Technologies
Mission Brief
Published in the Technix International Journal for Engineering Research, StyleForge investigates adversarial generative modeling (GANs) for high-resolution garment synthesis, texture translation, and style transfer across diverse body forms and fashion design aesthetics.
Key Features
Generative Adversarial Architecture
- Custom conditional GAN architecture optimized for textile pattern and drape fidelity.
- Loss formulation balancing structural boundary preservation with fine texture realism.
Visual Gallery
IMG_01
Project Access
Technologies
GANs
PyTorch
Computer Vision
Deep Learning
Generative AI
Table of Contents
- • Mission Brief
- • Key Features
- • Visual Gallery
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