AI-Assisted Art Critique Platform

Abstract: The current art critique platforms present two main problems which stem from their absence of AI-driven feedback system and their inability to assess all available media formats and their basic analytical capabilities and their lack of community features and personalization options. Accessibility and complete artist progress tracking systems receive insufficient attention from numerous organizations. The project seeks to develop an innovative art critique platform which uses AI-generated feedback to assess artistic progress through its ability to analyze multiple multimedia artwork formats which include images and videos and 3D models. The platform uses React.js for its frontend development and Node.js with Express.js for backend operations while employing MongoDB for database functions and Python (Flask) or external APIs to deliver AI-based assessments. The platform enables artists to create accounts which allow them to upload different artwork types while receiving immediate automated feedback through the integrated AI system. Users can engage in peer assessment activities, participate in collaborative critique discussions, and discover mentors who will assist them in their growth process. The system provides users with advanced analysis tools which enable them to track their development and skill growth throughout different periods, while the system's personalized critique matching, which works with its strong accessibility features, creates a welcoming space that accommodates artists from all backgrounds and skill levels.

Keywords: AI-assisted feedback, Multimedia artworks, In-depth analytics, Group critique sessions, Progress tracking, Personalized critique matching, Inclusive environment