Update README.md

README.md

@@ -31,7 +31,7 @@ library_name: MoG
  
 MoG is a generative video frame interpolation (VFI) model, designed to synthesize intermediate frames between two input frames.
 
-MoG marks the first explicit incorporation of motion guidance between input frames to enhance the motion awareness of generative models. We demonstrate that the intermediate flow derived from flow-based VFI methods can effectively serve as motion guidance, and we propose a simple yet efficient approach to integrate this prior into the network. As a result, MoG achieves significant improvements over existing open-source generative VFI methods, excelling in both real-world and animated scenarios.
+MoG is the first VFI framework to bridge the gap between flow-based stability and generative flexibility. We introduce a dual-level guidance injection design to constrain generated motion using motion trajectories derived from optical flow. To enhance the generative model's ability to dynamically correct flow errors, we implement encoder-only guidance injection and selective parameter fine-tuning. As a result, MoG achieves significant improvements over existing open-source generative VFI methods, delivering superior performance in both real-world and animated scenarios.
 
 Source code is available at [https://github.com/MCG-NJU/MoG-VFI](https://github.com/MCG-NJU/MoG-VFI).