mlsanityData to 7 Oct 2026

A Good Image Generator Is What You Need for High-Resolution Video Synthesis

arXiv 2104.15069 ↗First posted 30 Apr 2021cs.CVcited by 162

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Cited by 56 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Image and video synthesis are closely related areas aiming at generating content from noise. While rapid progress has been demonstrated in improving image-based models to handle large resolutions, high-quality renderings, and wide variations in image content, achieving comparable video generation results remains problematic. We present a framework that leverages contemporary image generators to render high-resolution videos. We frame the video synthesis problem as discovering a trajectory in the latent space of a pre-trained and fixed image generator. Not only does such a framework render high-resolution videos, but it also is an order of magnitude more computationally efficient. We introduce a motion generator that discovers the desired trajectory, in which content and motion are disentangled. With such a representation, our framework allows for a broad range of applications, including content and motion manipulation. Furthermore, we introduce a new task, which we call cross-domain video synthesis, in which the image and motion generators are trained on disjoint datasets belonging to different domains. This allows for generating moving objects for which the desired video data is not available. Extensive experiments on various datasets demonstrate the advantages of our methods over existing video generation techniques. Code will be released at https://github.com/snap-research/MoCoGAN-HD.

Key facts. Cited by 162 papers in the map (data through 7 Oct 2026). Builds on 66 of its 83 references that are in the map. First posted on arXiv 30 Apr 2021.

Builds on

66 of 83 references.

References · 66

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38 more
  1. 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,838
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  17. 2020GANSpace: Discovering Interpretable GAN Controlscited by 612
  18. 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 523
  19. 2020In-Domain GAN Inversion for Real Image Editingcited by 420
  20. 2020Closed-Form Factorization of Latent Semantics in GANscited by 407
  21. 2018Video-to-Video Synthesiscited by 388
  22. 2016Generating Videos with Scene Dynamicscited by 376
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50 most cited of 66 All 66 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 40; 2023: 51; 2024: 41; 2025: 18; 2026: 5.

162 papers.

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  1. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
  2. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
  3. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,465
  4. 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 973
  5. 2024Latte: Latent Diffusion Transformer for Video Generationcited by 536
  6. 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 463
  7. 2022Latent Video Diffusion Models for High-Fidelity Long Video Generationcited by 385
  8. 2023LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Modelscited by 349
  9. 2022MAGVIT: Masked Generative Video Transformercited by 341
  10. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  11. 2023Show-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generationcited by 300
  12. 2023Preserve Your Own Correlation: A Noise Prior for Video Diffusion Modelscited by 284
38 more
  1. 2024Champ: Controllable and Consistent Human Image Animation with 3D Parametric Guidancecited by 271
  2. 2022CelebV-HQ: A Large-Scale Video Facial Attributes Datasetcited by 246
  3. 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
  4. 2023SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Predictioncited by 231
  5. 2023A Survey on Video Diffusion Modelscited by 203
  6. 2022Generating Videos with Dynamics-aware Implicit Generative Adversarial Networkscited by 186
  7. 2023DreamVideo: Composing Your Dream Videos with Customized Subject and Motioncited by 186
  8. 2022Latent Image Animator: Learning to Animate Images via Latent Space Navigationcited by 172
  9. 2023MotionDirector: Motion Customization of Text-to-Video Diffusion Modelscited by 172
  10. 2023Video Probabilistic Diffusion Models in Projected Latent Spacecited by 171
  11. 2022StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGANcited by 169
  12. 2023Swap Attention in Spatiotemporal Diffusions for Text-to-Video Generationcited by 153
  13. 2025Diffusion Adversarial Post-Training for One-Step Video Generationcited by 142
  14. 2023Make Pixels Dance: High-Dynamic Video Generationcited by 140
  15. 2023Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generationcited by 137
  16. 2024ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generationcited by 130
  17. 2024OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generationcited by 117
  18. 2022Generating Long Videos of Dynamic Scenescited by 113
  19. 2024Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesiscited by 105
  20. 2023CelebV-Text: A Large-Scale Facial Text-Video Datasetcited by 103
  21. 2023SimDA: Simple Diffusion Adapter for Efficient Video Generationcited by 101
  22. 2023Motion-Conditioned Diffusion Model for Controllable Video Synthesiscited by 99
  23. 2023FreeInit: Bridging Initialization Gap in Video Diffusion Modelscited by 93
  24. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  25. 2023LLM-grounded Video Diffusion Modelscited by 83
  26. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  27. 2022VIDM: Video Implicit Diffusion Modelscited by 78
  28. 2023VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generationcited by 74
  29. 2024Vlogger: Make Your Dream A Vlogcited by 70
  30. 2021CCVS: Context-aware Controllable Video Synthesiscited by 68
  31. 2022Stitch it in Time: GAN-Based Facial Editing of Real Videoscited by 68
  32. 2024DrivingWorld: Constructing World Model for Autonomous Driving via Video GPTcited by 66
  33. 2021GAN-Supervised Dense Visual Alignmentcited by 61
  34. 2023Text2Performer: Text-Driven Human Video Generationcited by 53
  35. 2025AR-Diffusion: Asynchronous Video Generation with Auto-Regressive Diffusioncited by 53
  36. 2024On the Content Bias in Fr'echet Video Distancecited by 51
  37. 2023AutoDecoding Latent 3D Diffusion Modelscited by 50
  38. 2023Hierarchical Spatio-temporal Decoupling for Text-to-Video Generationcited by 50

50 most cited of 162 All 162 (JSON)