Visual Identity

Visual identity research focuses on understanding and manipulating how visual elements represent brands, individuals, or concepts. Current research employs machine learning, particularly deep learning models like diffusion models and large language models (LLMs), to analyze and generate visual identities, often focusing on logo recognition, brand-celebrity matching, and privacy-preserving techniques. These advancements have implications for brand protection (e.g., detecting phishing websites), personalized content generation, and ethical considerations surrounding data privacy in visual analytics. The development of interpretable models and robust algorithms is a key area of ongoing investigation.