Paper
AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist?
Authors
Hailong Yan, Shice Liu, Tao Wang, Xiangtao Zhang, Yijie Zhong, Jinwei Chen, Le Zhang, Bo Li
Abstract
Custom Storyboard Generation (CSG) aims to produce high-quality, multi-character consistent storytelling. Current approaches based on static diffusion models, whether used in a one-shot manner or within multi-agent frameworks, face three key limitations: (1) Static models lack dynamic expressiveness and often resort to "copy-paste" pattern. (2) One-shot inference cannot iteratively correct missing attributes or poor prompt adherence. (3) Multi-agents rely on non-robust evaluators, ill-suited for assessing stylized, non-realistic animation. To address these, we propose AnimeAgent, the first Image-to-Video (I2V)-based multi-agent framework for CSG. Inspired by Disney's "Combination of Straight Ahead and Pose to Pose" workflow, AnimeAgent leverages I2V'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.
Metadata
Related papers
Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini
Ruofei Du, Benjamin Hersh, David Li, Nels Numan, Xun Qian, Yanhe Chen, Zhongy... • 2026-03-25
Comparing Developer and LLM Biases in Code Evaluation
Aditya Mittal, Ryan Shar, Zichu Wu, Shyam Agarwal, Tongshuang Wu, Chris Donah... • 2026-03-25
The Stochastic Gap: A Markovian Framework for Pre-Deployment Reliability and Oversight-Cost Auditing in Agentic Artificial Intelligence
Biplab Pal, Santanu Bhattacharya • 2026-03-25
Retrieval Improvements Do Not Guarantee Better Answers: A Study of RAG for AI Policy QA
Saahil Mathur, Ryan David Rittner, Vedant Ajit Thakur, Daniel Stuart Schiff, ... • 2026-03-25
MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination
Zhuo Li, Yupeng Zhang, Pengyu Cheng, Jiajun Song, Mengyu Zhou, Hao Li, Shujie... • 2026-03-25
Raw Data (Debug)
{
"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2602.20664v1</id>\n <title>AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist?</title>\n <updated>2026-02-24T08:14:24Z</updated>\n <link href='https://arxiv.org/abs/2602.20664v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2602.20664v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>Custom Storyboard Generation (CSG) aims to produce high-quality, multi-character consistent storytelling. Current approaches based on static diffusion models, whether used in a one-shot manner or within multi-agent frameworks, face three key limitations: (1) Static models lack dynamic expressiveness and often resort to \"copy-paste\" pattern. (2) One-shot inference cannot iteratively correct missing attributes or poor prompt adherence. (3) Multi-agents rely on non-robust evaluators, ill-suited for assessing stylized, non-realistic animation. To address these, we propose AnimeAgent, the first Image-to-Video (I2V)-based multi-agent framework for CSG. Inspired by Disney's \"Combination of Straight Ahead and Pose to Pose\" workflow, AnimeAgent leverages I2V'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.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='cs.CV'/>\n <published>2026-02-24T08:14:24Z</published>\n <arxiv:comment>Tech Report</arxiv:comment>\n <arxiv:primary_category term='cs.CV'/>\n <author>\n <name>Hailong Yan</name>\n </author>\n <author>\n <name>Shice Liu</name>\n </author>\n <author>\n <name>Tao Wang</name>\n </author>\n <author>\n <name>Xiangtao Zhang</name>\n </author>\n <author>\n <name>Yijie Zhong</name>\n </author>\n <author>\n <name>Jinwei Chen</name>\n </author>\n <author>\n <name>Le Zhang</name>\n </author>\n <author>\n <name>Bo Li</name>\n </author>\n </entry>"
}