mlsanityData to 7 Oct 2026

Towards Smooth Video Composition

arXiv 2212.07413 ↗First posted 14 Dec 2022cs.CVcited by 12

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Abstract (arXiv)

Video generation requires synthesizing consistent and persistent frames with dynamic content over time. This work investigates modeling the temporal relations for composing video with arbitrary length, from a few frames to even infinite, using generative adversarial networks (GANs). First, towards composing adjacent frames, we show that the alias-free operation for single image generation, together with adequately pre-learned knowledge, brings a smooth frame transition without compromising the per-frame quality. Second, by incorporating the temporal shift module (TSM), originally designed for video understanding, into the discriminator, we manage to advance the generator in synthesizing more consistent dynamics. Third, we develop a novel B-Spline based motion representation to ensure temporal smoothness to achieve infinite-length video generation. It can go beyond the frame number used in training. A low-rank temporal modulation is also proposed to alleviate repeating contents for long video generation. We evaluate our approach on various datasets and show substantial improvements over video generation baselines. Code and models will be publicly available at https://genforce.github.io/StyleSV.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 59 of its 64 references that are in the map. First posted on arXiv 14 Dec 2022.

Builds on

59 of 64 references.

References · 59

  1. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  2. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  3. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  4. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  5. 2022Video Diffusion Modelscited by 2,280
  6. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
  7. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
  8. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  9. 2022CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformerscited by 973
  10. 2016Conditional Image Generation with PixelCNN Decoderscited by 859
  11. 2018TSM: Temporal Shift Module for Efficient Video Understandingcited by 852
  12. 2018Recurrent World Models Facilitate Policy Evolutioncited by 761
38 more
  1. 2020First Order Motion Model for Image Animationcited by 698
  2. 2021VideoGPT: Video Generation using VQ-VAE and Transformerscited by 651
  3. 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 523
  4. 2020InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANscited by 393
  5. 2018Video-to-Video Synthesiscited by 388
  6. 2016Generating Videos with Scene Dynamicscited by 376
  7. 2018Everybody Dance Nowcited by 313
  8. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  9. 2016Unsupervised Learning for Physical Interaction through Video Predictioncited by 256
  10. 2021GODIVA: Generating Open-DomaIn Videos from nAtural Descriptionscited by 254
  11. 2021N"UWA: Visual Synthesis Pre-training for Neural visUal World creAtioncited by 253
  12. 2019On the "steerability" of generative adversarial networkscited by 247
  13. 2022Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformercited by 244
  14. 2020Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Imagecited by 239
  15. 2022Diffusion Probabilistic Modeling for Video Generationcited by 237
  16. 2017Stochastic Variational Video Predictioncited by 234
  17. 2018Animating Arbitrary Objects via Deep Motion Transfercited by 206
  18. 2016Temporal Generative Adversarial Nets with Singular Value Clippingcited by 198
  19. 2019GANalyze: Toward Visual Definitions of Cognitive Image Propertiescited by 193
  20. 2019Scaling Autoregressive Video Modelscited by 189
  21. 2022Generating Videos with Dynamics-aware Implicit Generative Adversarial Networkscited by 186
  22. 2018Stochastic Adversarial Video Predictioncited by 173
  23. 2022Latent Image Animator: Learning to Animate Images via Latent Space Navigationcited by 172
  24. 2021A Good Image Generator Is What You Need for High-Resolution Video Synthesiscited by 162
  25. 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
  26. 2018Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GANcited by 120
  27. 2022Generating Long Videos of Dynamic Scenescited by 113
  28. 2016Video Pixel Networkscited by 108
  29. 2019Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesiscited by 106
  30. 2020Latent Video Transformercited by 106
  31. 2020Rewriting a Deep Generative Modelcited by 105
  32. 2017Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networkscited by 88
  33. 2020Learning to Simulate Dynamic Environments with GameGANcited by 86
  34. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  35. 2019VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generationcited by 74
  36. 2018Pose Guided Human Video Generationcited by 67
  37. 2020Transformation-based Adversarial Video Prediction on Large-Scale Datacited by 66
  38. 2021Predicting Video with VQVAEcited by 61

50 most cited of 59 All 59 (JSON)

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Cited by year

Citing papers per year: 2023: 7; 2024: 2; 2025: 3.

12 papers.

  1. 2023LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Modelscited by 349
  2. 2023Pix2Video: Video Editing using Image Diffusioncited by 318
  3. 2024VideoGigaGAN: Towards Detail-rich Video Super-Resolutioncited by 30
  4. 2023StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generationcited by 19
  5. 2024Urban Scene Diffusion through Semantic Occupancy Mapcited by 14
  6. 2023Image Synthesis under Limited Data: A Survey and Taxonomycited by 9
  7. 2023GenDeF: Learning Generative Deformation Field for Video Generationcited by 3
  8. 2025A Survey: Spatiotemporal Consistency in Video Generationcited by 3
  9. 2023Learning Modulated Transformation in GANscited by 1
  10. 2025GriDiT: Factorized Grid-Based Diffusion for Efficient Long Image Sequence Generationcited by 1
  11. 2023Improving Few-shot Image Generation by Structural Discrimination and Textural Modulationcited by 0
  12. 2025Inference-based GAN Video Generationcited by 0