Published Paper Details:

The "Mix'n'Match: Creative Image Generator" project introduces an innovative approach to image synthesis, harnessing the power of Hierarchical Code Representation for Image Generation (FineGAN) and Neural Style Transfer (NST). This platform empowers users to create unique and visually captivating images effortlessly by seamlessly blending components such as background, textures, shape, and color. Through the utilization of Fine GAN, the project ensures the generation of realistic and diverse elements, while NST enhances the artistic quality of the images, enabling the users to imbue their creations with distinctive visual styles. The platform's key components i.e, background, textures, shape, and color offer users unprecedented flexibility and control. Whether choosing from a library of predefined options or uploading personal elements, users can manipulate and customize each aspect of their images. Texture synthesis techniques provide the ability to apply various textures to different parts of the image, while shape customization allows users to select, adjust, or generate new shapes. With an intuitive user interface and the convergence of cutting-edge technologies, Mix'n'Match opens new avenues for creative expression, making image generation an accessible and dynamic process for individuals across various artistic backgrounds.