Workshop on Generative AI for Photography
Abstract
The camera serves as the primary visual interface between the real and the visual world, and a photograph captures a visual snapshot that contains rich physical concepts (e.g., illumination, blur). Meanwhile, generative AI has made significant progress in producing high-quality multi-modal content. However, current general Generative AI systems still have limited understanding of photographic concepts, which constrains their applicability to photography and cinematography. This gap is particularly critical, as photography and cinematography are not only influential art forms but also a complex multi-modal intellectual practice.Photography is a complex multi-modal intellectual practice. Capturing a photograph requires an agent to understand the environment, recognize the scene, compose the visual layout, compute and determine the appropriate camera settings, and trigger the shutter at the right moment. Scene understanding also involves recognizing the cultural and contextual significance of potential subjects. To compose the visual layout, the agent must select the field of view (FoV), which depends on the focal length and sensor size. To determine the camera settings, agents must reason about their visual outcomes. For example, depth of field (DoF) is jointly determined by aperture, focal length, and sensor size. Exposure depends on aperture, ISO speed, and shutter time, with the latter also influencing motion blur. Thus, photography requires integrated reasoning across perception, composition, and physics-based imaging principles. The Workshop on Generative AI for Photography (GAIP) aims to bridge general-purpose Generative AI with the domain knowledge of photography and cinematography. It unites researchers in vision, graphics, natural language processing, generative modeling, computational photography, and cognitive science to tackle challenges at the AI–arts intersection. GAIP will highlight new models, datasets, evaluation protocols, and benchmarks for systems that reason about composition, exposure, DoF, and visual storytelling. We expect that GAIP will advance AI research, drive real-world applications, democratize photographic expertise, and foster collaboration across academia, industry, and the creative community, making GAIP unique among WACV 2026 workshops.