mlsanityData to 7 Oct 2026

Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks

arXiv 2202.10571 ↗First posted 21 Feb 2022cs.CV cs.LGcited by 186

Not on the map. Why?

Cited by 78 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In the deep learning era, long video generation of high-quality still remains challenging due to the spatio-temporal complexity and continuity of videos. Existing prior works have attempted to model video distribution by representing videos as 3D grids of RGB values, which impedes the scale of generated videos and neglects continuous dynamics. In this paper, we found that the recent emerging paradigm of implicit neural representations (INRs) that encodes a continuous signal into a parameterized neural network effectively mitigates the issue. By utilizing INRs of video, we propose dynamics-aware implicit generative adversarial network (DIGAN), a novel generative adversarial network for video generation. Specifically, we introduce (a) an INR-based video generator that improves the motion dynamics by manipulating the space and time coordinates differently and (b) a motion discriminator that efficiently identifies the unnatural motions without observing the entire long frame sequences. We demonstrate the superiority of DIGAN under various datasets, along with multiple intriguing properties, e.g., long video synthesis, video extrapolation, and non-autoregressive video generation. For example, DIGAN improves the previous state-of-the-art FVD score on UCF-101 by 30.7% and can be trained on 128 frame videos of 128x128 resolution, 80 frames longer than the 48 frames of the previous state-of-the-art method.

Key facts. Cited by 186 papers in the map (data through 7 Oct 2026). Builds on 71 of its 89 references that are in the map. First posted on arXiv 21 Feb 2022.

Builds on

71 of 89 references.

References · 71

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  5. 2017Neural Discrete Representation Learningcited by 4,650
  6. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  7. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  8. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  9. 2016Improved Techniques for Training GANscited by 2,938
  10. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  11. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  12. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,170
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  1. 2017The Kinetics Human Action Video Datasetcited by 1,894
  2. 2017Improved Regularization of Convolutional Neural Networks with Cutoutcited by 1,623
  3. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
  4. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  5. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
  6. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  7. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  8. 2019CNN-generated images are surprisingly easy to spot... for nowcited by 842
  9. 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 750
  10. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  11. 2020First Order Motion Model for Image Animationcited by 698
  12. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  13. 2018Which Training Methods for GANs do actually Converge?cited by 672
  14. 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 651
  15. 2020Learning Continuous Image Representation with Local Implicit Image Functioncited by 550
  16. 2020Jukebox: A Generative Model for Musiccited by 535
  17. 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 523
  18. 2020Towards a Human-like Open-Domain Chatbotcited by 467
  19. 2015Unsupervised Learning of Video Representations using LSTMscited by 434
  20. 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
  21. 2016Generating Videos with Scene Dynamicscited by 376
  22. 2020Differentiable Augmentation for Data-Efficient GAN Trainingcited by 361
  23. 2021Generative Spoken Language Modeling from Raw Audiocited by 336
  24. 2018A Short Note about Kinetics-600cited by 331
  25. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  26. 2016Unsupervised Learning for Physical Interaction through Video Predictioncited by 256
  27. 2021NeRV: Neural Representations for Videoscited by 255
  28. 2018Stochastic Video Generation with a Learned Priorcited by 244
  29. 2017Stochastic Variational Video Predictioncited by 234
  30. 2021COIN: COmpression with Implicit Neural representationscited by 232
  31. 2016Temporal Generative Adversarial Nets with Singular Value Clippingcited by 198
  32. 2019Scaling Autoregressive Video Modelscited by 189
  33. 2018Stochastic Adversarial Video Predictioncited by 173
  34. 2017Decomposing Motion and Content for Natural Video Sequence Predictioncited by 168
  35. 2021A Good Image Generator Is What You Need for High-Resolution Video Synthesiscited by 162
  36. 2017Unsupervised Learning of Disentangled Representations from Videocited by 138
  37. 2020Adversarial Generation of Continuous Imagescited by 135
  38. 2018Learning to Decompose and Disentangle Representations for Video Predictioncited by 120

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Citing papers per year: 2022: 39; 2023: 64; 2024: 53; 2025: 24; 2026: 6.

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  19. 2025Diffusion Adversarial Post-Training for One-Step Video Generationcited by 142
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  25. 2023VDT: General-purpose Video Diffusion Transformers via Mask Modelingcited by 102
  26. 2023SimDA: Simple Diffusion Adapter for Efficient Video Generationcited by 101
  27. 2024Adaptive Caching for Faster Video Generation with Diffusion Transformerscited by 100
  28. 2023Human Motion Generation: A Surveycited by 95
  29. 2024MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Modelcited by 87
  30. 2023InstructVideo: Instructing Video Diffusion Models with Human Feedbackcited by 85
  31. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  32. 2022VIDM: Video Implicit Diffusion Modelscited by 78
  33. 2022E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Contextcited by 76
  34. 2023VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generationcited by 74
  35. 2025SkyReels-A2: Compose Anything in Video Diffusion Transformerscited by 72
  36. 2022Continuous PDE Dynamics Forecasting with Implicit Neural Representationscited by 71
  37. 2024Vlogger: Make Your Dream A Vlogcited by 70
  38. 2024Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharingcited by 70

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