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V’s implicit motion prior to enhance consistency and expressiveness, while a mixed subjective-objective reviewer enables reliable iterative refinement. We also collect a human-annotated CSG benchmark with ground-truth. Experiments show AnimeAgent achieves SOTA performance in consistency, prompt fidelity, and stylization. AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist? Hailong Yan1,2, Shice Liu2, Tao Wang2, Xiangtao Zhang1
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Fixed guidance weights in diffusion models are suboptimal: C$^2$FG offers a training-free, theoretically grounded approach to dynamically adjust guidance strength, improving performance across diverse generative tasks.
Image-to-video models can now generate more consistent and expressive animated storyboards than static diffusion models, thanks to a Disney-inspired multi-agent framework.
