Aether Annotator
The Video AETHER project focused on preparing high-quality visual training data to improve how AI models understand and interpret video content. My work involved reviewing video clips frame by frame, identifying key objects, actions, and contextual details, and accurately labeling them according to strict annotation guidelines. This included detecting scene changes, tagging motion or interactions, and ensuring that each annotation captured both what was happening and the context in which it occurred. A big part of the role was maintaining consistency and precision across large volumes of data while adapting to evolving project requirements. I also performed quality checks to validate annotations, corrected inconsistencies, and ensured that outputs aligned with model training standards. Through this project, I strengthened my ability to analyze visual data critically, follow complex guidelines, and contribute to building reliable datasets that directly improve AI model performance.