US20240221259
2024-07-04
Physics
G06T13/40
The technology focuses on generating realistic virtual hairstyles by utilizing a Generative Adversarial Network (GAN) model. Initially, a first image of a face is created using the GAN model. Subsequently, 3D virtual hair is applied to this image, resulting in a second image featuring the virtual hair. The second image is then projected into a GAN latent space to produce a third image that showcases realistic virtual hair.
The final step involves blending the realistic virtual hair from the third image with the original face image. This process results in a new image that presents a realistic hairstyle corresponding to the previously applied 3D virtual hair. A trained neural network facilitates this transformation, taking the second image with 3D virtual hair as input and generating an output image with realistic hair.
The rise of digital images and advancements in portable computing devices have transformed how users capture and share images. Augmented reality (AR) technology plays a significant role in enhancing user experiences by integrating electronic information with real-world environments. However, processing images under varying conditions remains challenging and resource-intensive.
The technology can be applied across various domains, including entertainment, gaming, and virtual conversations. It allows for content manipulation in real-time scenarios such as video calls or interactive media sharing. Users can interact with augmented reality content seamlessly, enhancing their engagement with digital images.
The underlying infrastructure supports an interaction system that includes multiple client systems connected over a network. This system enables data exchange between clients and servers, allowing for real-time communication and media sharing. The architecture includes features such as APIs for accessing server functionalities, facilitating user interactions, and managing multimedia content efficiently.