humanaigc/animateanyone

Analysis updated 2026-06-24

★ 14,772Audience · researcherComplexity · 2/5Setup · hard

Mindmap

mindmap
  root((AnimateAnyone))
    Inputs
      Single character image
      Pose or motion signal
    Outputs
      Animated video
      Consistent character frames
    Use Cases
      Read the paper
      Cite the work
      Track follow-up Wan-Animate
    Tech Stack
      Research code
      Diffusion models

mindmap root((AnimateAnyone)) Inputs Single character image Pose or motion signal Outputs Animated video Consistent character frames Use Cases Read the paper Cite the work Track follow-up Wan-Animate Tech Stack Research code Diffusion models

Click or tap to explore — scroll the page freely

What do people build with it?

USE CASE 1

Read the paper for character image-to-video synthesis techniques

USE CASE 2

Cite AnimateAnyone in academic work

USE CASE 3

Follow links to the Wan-Animate follow-up project for runnable code

What is it built with?

DiffusionPyTorchResearch

How does it compare?

	humanaigc/animateanyone	borisdayma/dalle-mini	spacehuhntech/esp8266_deauther
Stars	14,772	14,771	14,769
Language	—	Python	C
Setup difficulty	hard	hard	moderate
Complexity	2/5	4/5	3/5
Audience	researcher	researcher	developer

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1day+

Repo is a paper landing page only, no model weights, training code, or inference scripts are released here.

In plain English

AnimateAnyone is a research project from Alibaba's HumanAIGC group that accompanies a paper titled Animate Anyone: Consistent and Controllable Image-to-Video Synthesis for Character Animation. The repository's README is essentially a landing page for that paper. The subject is image-to-video synthesis: starting from a single still image of a character and generating a video that animates them in a consistent and controllable way. The README itself does not contain code, installation instructions, or usage examples. It lists the authors of the paper, Li Hu, Xin Gao, Peng Zhang, Ke Sun, Bang Zhang, and Liefeng Bo, with links to their academic profiles. There are three badges at the top: a link to the project page on humanaigc.github.io, a link to the paper PDF on arXiv with the identifier 2311.17117, and a link to a YouTube video. There is one announcement in the README. It points readers at a follow-up open-source project from the same group called Wan-Animate, which is described as part of the Animate Anyone series. The rest of the page is a teaser image and a BibTeX citation block for academic use. Anyone looking for the actual model weights, training code, or inference scripts will not find them in this README.

Copy-paste prompts

Prompt 1

Summarize the AnimateAnyone paper's core method in plain English

Prompt 2

Compare AnimateAnyone to other image-to-video character animation papers

Prompt 3

Find the closest open-source follow-up project to AnimateAnyone that ships weights

Prompt 4

Extract the BibTeX entry for AnimateAnyone for my paper

Frequently asked questions

What is animateanyone?

Research paper landing page for AnimateAnyone, an Alibaba image-to-video model that animates a still character image in a consistent, controllable way.

How hard is animateanyone to set up?

Setup difficulty is rated hard, with roughly 1day+ to a first successful run.

Who is animateanyone for?

Mainly researcher.

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