mlsanityData to 7 Oct 2026

Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks

arXiv 1709.07592 ↗First posted 22 Sep 2017cs.CVcited by 88

Not on the map. Why?

Cited by 33 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Taking a photo outside, can we predict the immediate future, e.g., how would the cloud move in the sky? We address this problem by presenting a generative adversarial network (GAN) based two-stage approach to generating realistic time-lapse videos of high resolution. Given the first frame, our model learns to generate long-term future frames. The first stage generates videos of realistic contents for each frame. The second stage refines the generated video from the first stage by enforcing it to be closer to real videos with regard to motion dynamics. To further encourage vivid motion in the final generated video, Gram matrix is employed to model the motion more precisely. We build a large scale time-lapse dataset, and test our approach on this new dataset. Using our model, we are able to generate realistic videos of up to 128× 128 resolution for 32 frames. Quantitative and qualitative experiment results have demonstrated the superiority of our model over the state-of-the-art models.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2017.

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Citing papers per year: 2021: 9; 2022: 14; 2023: 19; 2024: 29; 2025: 12; 2026: 5.

88 papers.

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  1. 2024Latte: Latent Diffusion Transformer for Video Generationcited by 536
  2. 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 463
  3. 2022Latent Video Diffusion Models for High-Fidelity Long Video Generationcited by 385
  4. 2024OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generationcited by 332
  5. 2023VideoFusion: Decomposed Diffusion Models for High-Quality Video Generationcited by 330
  6. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  7. 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
  8. 2024Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modelingcited by 209
  9. 2023A Survey on Video Diffusion Modelscited by 203
  10. 2022Generating Videos with Dynamics-aware Implicit Generative Adversarial Networkscited by 186
  11. 2023Conditional Image-to-Video Generation with Latent Flow Diffusion Modelscited by 180
  12. 2023Video Probabilistic Diffusion Models in Projected Latent Spacecited by 171
38 more
  1. 2021A Good Image Generator Is What You Need for High-Resolution Video Synthesiscited by 162
  2. 2022Generating Long Videos of Dynamic Scenescited by 113
  3. 2023VDT: General-purpose Video Diffusion Transformers via Mask Modelingcited by 102
  4. 2023SimDA: Simple Diffusion Adapter for Efficient Video Generationcited by 101
  5. 2021Make It Move: Controllable Image-to-Video Generation with Text Descriptionscited by 88
  6. 2024MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Modelcited by 87
  7. 2024Video as the New Language for Real-World Decision Makingcited by 86
  8. 2022VIDM: Video Implicit Diffusion Modelscited by 78
  9. 2023VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generationcited by 74
  10. 2024ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generationcited by 74
  11. 2023AnimateAnything: Fine-Grained Open Domain Image Animation with Motion Guidancecited by 66
  12. 2021Predicting Video with VQVAEcited by 61
  13. 2024WF-VAE: Enhancing Video VAE by Wavelet-Driven Energy Flow for Latent Video Diffusion Modelcited by 55
  14. 2025AR-Diffusion: Asynchronous Video Generation with Auto-Regressive Diffusioncited by 53
  15. 2024Follow-Your-Click: Open-domain Regional Image Animation via Short Promptscited by 52
  16. 2024MagicTime: Time-lapse Video Generation Models as Metamorphic Simulatorscited by 51
  17. 2024On the Content Bias in Fr'echet Video Distancecited by 51
  18. 2021Stochastic Image-to-Video Synthesis using cINNscited by 49
  19. 2024Improved Video VAE for Latent Video Diffusion Modelcited by 46
  20. 2021Controllable Animation of Fluid Elements in Still Imagescited by 44
  21. 2024Moonshot: Towards Controllable Video Generation and Editing with Multimodal Conditionscited by 42
  22. 2024A Survey on Long Video Generation: Challenges, Methods, and Prospectscited by 40
  23. 2023MoStGAN-V: Video Generation with Temporal Motion Stylescited by 37
  24. 2022Scientific and Technological Information Oriented Semantics-adversarial and Media-adversarial Cross-media Retrievalcited by 33
  25. 2024TRIP: Temporal Residual Learning with Image Noise Prior for Image-to-Video Diffusion Modelscited by 30
  26. 2024OD-VAE: An Omni-dimensional Video Compressor for Improving Latent Video Diffusion Modelcited by 30
  27. 2024Video Diffusion Models: A Surveycited by 28
  28. 2024Matten: Video Generation with Mamba-Attentioncited by 24
  29. 20233D Cinemagraphy from a Single Imagecited by 23
  30. 2023LaMD: Latent Motion Diffusion for Image-Conditional Video Generationcited by 21
  31. 2024Beyond FVD: Enhanced Evaluation Metrics for Video Generation Qualitycited by 21
  32. 2023StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generationcited by 19
  33. 2024Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approachcited by 18
  34. 2025X-Dyna: Expressive Dynamic Human Image Animationcited by 18
  35. 20223D-Aware Video Generationcited by 17
  36. 2024DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representationscited by 16
  37. 2025LeanVAE: An Ultra-Efficient Reconstruction VAE for Video Diffusion Modelscited by 15
  38. 2023Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Imagescited by 14

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