Wan CineScale lora-high resolution-KJ

Although visual diffusion models have progressed rapidly, the scarcity of high‑resolution training data and the high computational cost mean most systems are trained at relatively low resolutions (e.g., 512×512). Consequently, high‑fidelity image/video synthesis often suffers from texture repetition and loss of fine details; once the target resolution exceeds the training regime, the added high‑frequency content amplifies cumulative errors, further degrading visual quality.

an inference strategy tailored for high‑resolution generation. Without tedious tuning, it allows pretrained diffusion models to surpass resolution ceilings, covering text‑to‑image and text‑to‑video while extending to image‑to‑video and video‑to‑video. Empirically, it can produce 8K images with zero fine‑tuning and achieve 4K video with minimal LoRA adaptation, offering a cost‑effective path to high‑resolution results for film and visual design workflows.