mlsanityData to 7 Oct 2026

Real-time Diverse Motion In-betweening with Space-time Control

arXiv 2410.00270 ↗First posted 30 Sep 2024cs.GR cs.LGcited by 4

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Abstract (arXiv)

In this work, we present a data-driven framework for generating diverse in-betweening motions for kinematic characters. Our approach injects dynamic conditions and explicit motion controls into the procedure of motion transitions. Notably, this integration enables a finer-grained spatial-temporal control by allowing users to impart additional conditions, such as duration, path, style, etc., into the in-betweening process. We demonstrate that our in-betweening approach can synthesize both locomotion and unstructured motions, enabling rich, versatile, and high-quality animation generation.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 18 of its 41 references that are in the map. First posted on arXiv 30 Sep 2024.

Builds on

18 of 41 references.

References · 18

  1. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,186
  2. 2022Human Motion Diffusion Modelcited by 1,062
  3. 2019Confident Learning: Estimating Uncertainty in Dataset Labelscited by 411
  4. 2022EDGE: Editable Dance Generation From Musiccited by 284
  5. 2023OmniControl: Control Any Joint at Any Time for Human Motion Generationcited by 233
  6. 2021Robust Motion In-betweeningcited by 223
  7. 2023Guided Motion Diffusion for Controllable Human Motion Synthesiscited by 221
  8. 2022Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Modelscited by 188
  9. 2021Character Controllers Using Motion VAEscited by 182
  10. 2022Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phasescited by 71
  11. 2024Flexible Motion In-betweening with Diffusion Modelscited by 69
  12. 2018Recurrent Transition Networks for Character Locomotioncited by 52
6 more
  1. 2019MoGlow: Probabilistic and controllable motion synthesis using normalising flowscited by 47
  2. 2024Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfercited by 30
  3. 2022Real-time Controllable Motion Transition for Characterscited by 29
  4. 2023Motion In-Betweening with Phase Manifoldscited by 25
  5. 2022GANimator: Neural Motion Synthesis from a Single Sequencecited by 23
  6. 2023RSMT: Real-time Stylized Motion Transition for Characterscited by 19

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Cited by year

Citing papers per year: 2025: 4.

4 papers.

  1. 2025Towards Robust and Controllable Text-to-Motion via Masked Autoregressive Diffusioncited by 6
  2. 2025SILK: Smooth InterpoLation frameworK for motion in-betweening A Simplified Computational Approachcited by 1
  3. 2025PMG: Progressive Motion Generation via Sparse Anchor Postures Curriculum Learningcited by 0
  4. 2025Motion In-Betweening for Densely Interacting Characterscited by 0