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

UniGenDet is a unified generative-discriminative framework that co-evolves image generation and generated image detection, aligning generation with detector-aware signals for improved authenticity and robustness. It addresses the traditional separation where generators focus on perceptual realism while detectors react to a moving target by training on snapshots of existing forgeries, creating a persistent detection lag. The framework uses a symbiotic multimodal self-attention mechanism and unified fine-tuning algorithm to bridge generation and detection, enabling the generation task to improve authenticity identification interpretability while authenticity criteria guide higher-fidelity image creation.

Source: r/StableDiffusion | 2026-04-29