DragAnything: Motion Control for Anything using Entity Representation

Wejia Wu, Zhuang Li, Yuchao Gu, Rui Zhao, Yefei He +5 more
2/14/2026

No official code found. Best implementation: showlab/DragAnything (506 stars, last commit 2024-07-02).

Abstract

We introduce DragAnything, which utilizes a entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control methods, DragAnything offers several advantages. Firstly, trajectory-based is more userfriendly for interaction, when acquiring other guidance signals (e.g., masks, depth maps) is labor-intensive. Users only need to draw a line (trajectory) during interaction. Secondly, our entity representation serves as an open-domain embedding capable of representing any object, enabling the control of motion for diverse entities, including background. Lastly, our entity representation allows simultaneous and distinct motion control for multiple objects. Extensive experiments demonstrate that our DragAnything achieves state-of-the-art performance for FVD, FID, and User Study, particularly in terms of object motion control, where our method surpasses the previous methods (e.g., DragNUWA) by 26% in human voting.

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Code Implementations(1)

[ECCV 2024] DragAnything: Motion Control for Anything using Entity Representation

50617Shell, PythonMar 5, 20242 years ago

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Cite this paper

@article{wu2026draganything,
  title  = {DragAnything: Motion Control for Anything using Entity Representation},
  author = {Wejia Wu and Zhuang Li and Yuchao Gu and Rui Zhao and Yefei He and David Junhao Zhang and Mike Zheng Shou and Yan Li and Tingting Gao and Di Zhang},
  year   = {2026},
  eprint = {2403.07420},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2403.07420},
  journal = {ECCV 2024 2024}
}

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