Generative Pipeline

Generative pipelines are automated workflows combining multiple AI models to create complex outputs from various inputs, such as text, sketches, or images. Current research focuses on improving the reasoning capabilities of these pipelines, particularly for multi-concept generation and handling out-of-distribution data, often employing techniques like latent diffusion models, GANs, and combinatorial optimization. These advancements are impacting diverse fields, including robotics (through natural motion generation), fashion design (via garment synthesis), and image processing (with improved colorization and texture generation), by enabling more efficient and creative content creation.