Sketch Generation

Sketch generation research focuses on algorithmically creating drawings, aiming to replicate human-like artistic styles and capture object semantics. Current efforts leverage various deep learning architectures, including transformers, diffusion models, and implicit neural representations, often incorporating techniques like differentiable rendering and multi-modal fusion to improve realism and controllability. This field is significant for its potential applications in various domains, such as computer-aided design, image editing, and creative content generation, while also advancing our understanding of visual perception and artistic processes. The development of large-scale datasets and standardized evaluation metrics is driving progress towards more robust and versatile sketch generation models.