Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation
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Cited by 31 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of existing video clips and synthesize a coherent storytelling video by customizing their appearances. We achieve this by developing a framework comprised of two functional modules: (i) Motion Structure Retrieval, which provides video candidates with desired scene or motion context described by query texts, and (ii) Structure-Guided Text-to-Video Synthesis, which generates plot-aligned videos under the guidance of motion structure and text prompts. For the first module, we leverage an off-the-shelf video retrieval system and extract video depths as motion structure. For the second module, we propose a controllable video generation model that offers flexible controls over structure and characters. The videos are synthesized by following the structural guidance and appearance instruction. To ensure visual consistency across clips, we propose an effective concept personalization approach, which allows the specification of the desired character identities through text prompts. Extensive experiments demonstrate that our approach exhibits significant advantages over various existing baselines.
Key facts. Cited by 90 papers in the map (data through 14 Oct 2026). Builds on 42 of its 46 references that are in the map. First posted on arXiv 13 Jul 2023.
Builds on
42 of 46 references.
References · 42
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- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
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- 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
- 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
- 2022Video Diffusion Modelscited by 2,305
- 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
- 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,778
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- 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,495
- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,476
- 2021Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrievalcited by 1,177
- 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,106
- 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 985
- 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorscited by 670
- 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 658
- 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 524
- 2022Phenaki: Variable Length Video Generation From Open Domain Textual Descriptioncited by 484
- 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 465
- 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 464
- 2023ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generationcited by 416
- 2016Generating Videos with Scene Dynamicscited by 376
- 2022MAGVIT: Masked Generative Video Transformercited by 346
- 2023VideoFusion: Decomposed Diffusion Models for High-Quality Video Generationcited by 331
- 2023ControlVideo: Training-free Controllable Text-to-Video Generationcited by 327
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- 2023Composer: Creative and Controllable Image Synthesis with Composable Conditionscited by 304
- 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 301
- 2021GODIVA: Generating Open-DomaIn Videos from nAtural Descriptionscited by 256
- 2023Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translationcited by 253
- 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
- 2016Temporal Generative Adversarial Nets with Singular Value Clippingcited by 198
- 2022Sketch-Guided Text-to-Image Diffusion Modelscited by 180
- 2023Video Probabilistic Diffusion Models in Projected Latent Spacecited by 171
- 2023Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoisingcited by 139
- 2023Make-Your-Video: Customized Video Generation Using Textual and Structural Guidancecited by 129
- 2023A Neural Space-Time Representation for Text-to-Image Personalizationcited by 123
- 2022VIDM: Video Implicit Diffusion Modelscited by 78
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Citing papers per year: 2023: 11; 2024: 36; 2025: 33; 2026: 10.
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