Wiener-Informed Decoding Accelerates Pixel-Space Flow Model Training

Wiener-Informed Decoding (WiD) uses frozen second-order image statistics to improve velocity field learning in pixel-space flow models. The method injects statistical knowledge into native decoders via a trainable Wiener prediction path and coefficient interfaces without modifying the original architecture blocks.