scene long
videos. This detailed guidance works with a Frame-Level Attention Mechanism to
make sure text and video match precisely. A key feature is that each part
(frame) within these windows can be guided by its own distinct text prompt. Our
training uses Diffusion Forcing to provide the model with the ability to handle
time flexibly. We tested our approach on difficult VBench 2.0 benchmarks
("Complex Plots" and "Complex Landscapes") based on the WanX2.1-T2V-1.3B model.
The results show our method is bett