Image Analysis & Quality Annotator, TrainAI
Assessed face-swap images against generative image quality and annotation guidelines to support model improvement. Evaluated realism, alignment, and overall visual integrity while flagging artifacts, distortions, and inconsistencies. Provided quality-focused judgment to ensure annotated outputs meet strict requirements for downstream training. • Realism and alignment evaluation for face-swap outputs • Detection of visual artifacts, distortions, and inconsistencies • Application of image quality/annotation guidelines • Contribution to generative model improvement through quality signals