A Survey on Long-Video Storytelling Generation: Architectures,
  Consistency, and Cinematic Quality
Despite the significant progress that has been made in video generative
models, existing state-of-the-art methods can only produce videos lasting 5-16
seconds, often labeled "long-form videos". Furthermore, videos exceeding 16
seconds struggle to maintain consistent character appearances and scene layouts
throughout the narrative. In particular, multi-subject long videos still fail
to preserve character consistency and motion coherence. While some methods can
generate videos up to 150 seconds long, they often suffer from frame redundancy
and low temporal diversity. Recent work has attempted to produce long-form
videos featuring multiple characters, narrative coherence, and high-fidelity
detail. We comprehensively studied 32 papers on video generation to identify
key architectural components and training strategies that consistently yield
these qualities. We also construct a comprehensive novel taxonomy of existing
methods and present comparative tables that categorize papers by their
architectural designs and performance characteristics.
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Mohamed Elmoghany
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2025-07-11T08:00:12.603Z
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Mohamed Elmoghany
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elmoghany
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Ryan Rossi
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Seunghyun Yoon
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Subhojyoti Mukherjee
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Eslam Bakr
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Puneet Mathur
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Gang Wu
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Viet Dac Lai
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Nedim Lipka
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Ruiyi Zhang
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Varun Manjunatha
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Chien Nguyen
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Daksh Dangi
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Abel Salinas
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Mohammad Taesiri
claimed_verified
2025-07-11T08:00:08.440Z
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taesiri
user
taesiri
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Hongjie Chen
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Xiaolei Huang
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Joe Barrow
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Nesreen Ahmed
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Hoda Eldardiry
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Namyong Park
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Yu Wang
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Jaemin Cho
claimed_verified
2025-07-11T16:31:58.647Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/1654821969191-5ffe32d8942cf3533d364449.jpeg
Jaemin Cho
user
j-min
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Anh Totti Nguyen
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Zhengzhong Tu
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Thien Nguyen
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Dinesh Manocha
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Mohamed Elhoseiny
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Franck Dernoncourt
claimed_verified
2025-07-11T08:00:10.400Z
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Franck Dernoncourt
user
Franck-Dernoncourt
A Survey on Long-Video Storytelling Generation: Architectures,
  Consistency, and Cinematic Quality
Despite the significant progress that has been made in video generative
models, existing state-of-the-art methods can only produce videos lasting 5-16
seconds, often labeled "long-form videos". Furthermore, videos exceeding 16
seconds struggle to maintain consistent character appearances and scene layouts
throughout the narrative. In particular, multi-subject long videos still fail
to preserve character consistency and motion coherence. While some methods can
generate videos up to 150 seconds long, they often suffer from frame redundancy
and low temporal diversity. Recent work has attempted to produce long-form
videos featuring multiple characters, narrative coherence, and high-fidelity
detail. We comprehensively studied 32 papers on video generation to identify
key architectural components and training strategies that consistently yield
these qualities. We also construct a comprehensive novel taxonomy of existing
methods and present comparative tables that categorize papers by their
architectural designs and performance characteristics.
Research identifies key components and strategies for generating long-form videos with multiple characters, narrative coherence, and high-fidelity detail.
video generative models long-form videos character consistency scene layouts motion coherence frame redundancy temporal diversity architectural components training strategies taxonomy