DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors
On the map: Diffusion models → Video generation
Abstract (arXiv)
Animating a still image offers an engaging visual experience. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds and fluid) or domain-specific motions (e.g. human hair or body motions), and thus limits their applicability to more general visual content. To overcome this limitation, we explore the synthesis of dynamic content for open-domain images, converting them into animated videos. The key idea is to utilize the motion prior of text-to-video diffusion models by incorporating the image into the generative process as guidance. Given an image, we first project it into a text-aligned rich context representation space using a query transformer, which facilitates the video model to digest the image content in a compatible fashion. However, some visual details still struggle to be preserved in the resultant videos. To supplement with more precise image information, we further feed the full image to the diffusion model by concatenating it with the initial noises. Experimental results show that our proposed method can produce visually convincing and more logical & natural motions, as well as higher conformity to the input image. Comparative evaluation demonstrates the notable superiority of our approach over existing competitors.
Key facts. Cited by 471 papers in the map (data through 14 Oct 2026). Placed in Video generation, one of 14 directions in Diffusion models. Builds on 79 of its 105 references that are in the map. First posted on arXiv 18 Oct 2023.
Builds on
79 of 105 references.
Closest ancestors · 17
Same direction, newest first
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- 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models18 Apr
- 2023Conditional Image-to-Video Generation with Latent Flow Diffusion Models24 Mar
- 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators23 Mar
- 2023VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation15 Mar
- 2023Structure and Content-Guided Video Synthesis with Diffusion Models6 Feb
- 2023Dreamix: Video Diffusion Models are General Video Editors2 Feb
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- 2022MagicVideo: Efficient Video Generation With Latent Diffusion Models20 Nov
- 2022Imagen Video: High Definition Video Generation with Diffusion Models5 Oct
- 2022Diffusion Models for Video Prediction and Infilling15 Jun
- 2022MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation19 May
- 2022Video Diffusion Models7 Apr
Other references · 62
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2020Denoising Diffusion Implicit Modelscited by 9,781
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,585
- 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
- 2022Classifier-Free Diffusion Guidancecited by 5,847
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
- 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
- 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
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- 2016Gaussian Error Linear Units (GELUs)cited by 3,502
- 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,742
- 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,464
- 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,351
- 2021Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrievalcited by 1,177
- 2021Perceiver: General Perception with Iterative Attentioncited by 1,104
- 2017The 2017 DAVIS Challenge on Video Object Segmentationcited by 957
- 2020First Order Motion Model for Image Animationcited by 704
- 2023OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Modelscited by 565
- 2022Phenaki: Variable Length Video Generation From Open Domain Textual Descriptioncited by 484
- 2023VideoComposer: Compositional Video Synthesis with Motion Controllabilitycited by 464
- 2019SinGAN: Learning a Generative Model from a Single Natural Imagecited by 348
- 2022MAGVIT: Masked Generative Video Transformercited by 346
- 2023InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuningcited by 345
- 2023Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videoscited by 314
- 2023DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectorycited by 264
- 2021Motion Representations for Articulated Animationcited by 255
- 2023P+: Extended Textual Conditioning in Text-to-Image Generationcited by 242
- 2017Stochastic Variational Video Predictioncited by 234
- 2022Thin-Plate Spline Motion Model for Image Animationcited by 210
- 2018Animating Arbitrary Objects via Deep Motion Transfercited by 208
- 2023JourneyDB: A Benchmark for Generative Image Understandingcited by 205
- 2023Any-to-Any Generation via Composable Diffusioncited by 204
- 2022Latent Image Animator: Learning to Animate Images via Latent Space Navigationcited by 175
- 2018Stochastic Adversarial Video Predictioncited by 173
- 2023DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusioncited by 167
- 2023Make-Your-Video: Customized Video Generation Using Textual and Structural Guidancecited by 129
- 2023ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Modelscited by 128
- 2020Stochastic Latent Residual Video Predictioncited by 108
- 2023Generative Image Dynamicscited by 94
- 2017Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networkscited by 89
- 2021Make It Move: Controllable Image-to-Video Generation with Text Descriptionscited by 88
- 2020Improving Image Captioning with Better Use of Captionscited by 84
- 2020Improved Techniques for Training Single-Image GANscited by 78
- 2018Photo Wake-Up: 3D Character Animation from a Single Photocited by 60
- 2018Flow-Grounded Spatial-Temporal Video Prediction from Still Imagescited by 55
- 2020Animating Pictures with Eulerian Motion Fieldscited by 55
- 2023A Dynamic Multi-Scale Voxel Flow Network for Video Predictioncited by 53
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Citing papers per year: 2023: 8; 2024: 139; 2025: 224; 2026: 100.
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