UniGenDet - A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection.

Image generation and generated-image detection have both advanced rapidly, but mostly along separate technical paths: generation is dominated by generative architectures, while detection is dominated by discriminative ones. This separation creates a persistent gap in practice: generators are not directly optimized by forensic criteria, and detectors are often trained on static snapshots of old forgeries, which limits robustness to new generators. UniGenDet addresses this gap with a unified co-evolutionary framework that jointly optimizes generation and detection in one loop.