AI RESEARCH
Spectral and Trajectory Regularization for Diffusion Transformer Super-Resolution
arXiv CS.CV
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ArXi:2603.06275v1 Announce Type: new Diffusion transformer (DiT) architectures show great potential for real-world image super-resolution (Real-ISR). However, their computationally expensive iterative sampling necessitates one-step distillation. Existing one-step distillation methods struggle with Real-ISR on DiT. They suffer from fundamental trajectory mismatch and generate severe grid-like periodic artifacts. To tackle these challenges, we propose StrSR, a novel one-step adversarial distillation framework featuring spectral and trajectory regularization.