Journal of Visual Artificial Intelligence is an open access, single blind, peer reviewed, quarterly publication focused on promoting state-of-the-art research at the interplay of computer vision, visual computing and artificial intelligence. The journal serves as a platform for high-quality research on how intelligent visual systems perceive, process, interpret, and interact with the world, spanning both fundamental theory and mission-critical applications.

The journal focuses on the core methodologies of AI, as well as on next-generation visual technologies. It has a well-rounded but integrated range of topics, such as image and video understanding, pattern recognition, multimodal learning, generative visual models, autonomous system perception, and human-AI visual interaction. It also features new areas of explainable visual AI, embodied visual intelligence and ethics-motivated system design.

The Journal of Visual Artificial Intelligence is a high-tech journal that targets the needs of scholars, innovators, engineers, and industry professionals interested in knowing and extending the limits of machine vision. The journal explains how smart visual systems can propel innovations in key areas, such as autonomous mobility, robotics, healthcare diagnostics, digital media, security and surveillance, augmented and virtual reality, and environmental monitoring.