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What you can do with 4DAnyone

4DAnyone is a Python research repo that turns a casual monocular video of one person into consistent multiview videos for downstream 4D Gaussian Splatting reconstruction.

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ant-research/4DAnyone on GitHub

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What do you want to do?

3 use cases

  • Turn a casual clip into a 24-view orbit set

    Generate 24 consistent target-view videos of one person from a single monocular video.

    View prompt
    In the 4DAnyone repo, replace the example video path with <video_path> and run inference.py with --views_per_layer 24 writing to <output_dir>. Expected output: cameras.json, skeletons/, and videos/ with 24 target videos. Verify that cameras.json lists 24 views and videos/ contains 24 .mp4 files.

  • Preview camera layouts in a browser GUI

    Run the Gradio GUI to inspect inference results and visualize target views with Rerun.

    View prompt
    In the 4DAnyone repo, run app.py with --output_dir set to <output_dir> and --server_port 7860, then confirm the Gradio page loads at http://127.0.0.1:7860. Expected output: an interactive view of the inference results. Verify that the output directory contains cameras.json and videos/ before launching.

  • Run a quick 6-view test on a consumer GPU

    Produce a compact 360 degree six-view set with the Turbo default to check the pipeline works.

    View prompt
    In the 4DAnyone repo, run scripts/download_example.py and then inference.py with --views_per_layer 6 on the example video, writing to <output_dir>. Expected output: six target videos and cameras.json. Verify that videos/ holds 6 .mp4 files and that metadata.json records the run settings.

How to use 4DAnyone

  1. Check you have what it needs: A CUDA-capable NVIDIA GPU (README cites peak use below 24 GB and an RTX 4090 benchmark); Git and conda installed; A source video that is a single person, 1080p or higher, 9:16 portrait, at least 121 frames.
  2. Open ant-research/4DAnyone on GitHub and read the README and license.
  3. git clone https://github.com/ant-research/4DAnyone.git
  4. cd 4DAnyone
  5. git submodule update --init third_party/GVHMR
  6. conda create -n 4danyone python=3.11 -y then conda activate 4danyone

These steps come from our top use case, Turn a casual clip into a 24-view orbit set, which also has a copy-paste agent prompt.

4DAnyone alternatives · Best AI repos for Research

About this repo

  • Who it is forBuilt for researchers and developers with an NVIDIA GPU who want to generate multiview videos of a person from a single phone or casual video.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/ant-research/4DAnyone · Back to Hot repos

Requirements

  • A CUDA-capable NVIDIA GPU (README cites peak use below 24 GB and an RTX 4090 benchmark)
  • Git and conda installed
  • A source video that is a single person, 1080p or higher, 9:16 portrait, at least 121 frames
  • Permission to use the person shown in the source video
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Questions about 4DAnyone

What is 4DAnyone?

4DAnyone is a Python research repo that turns a casual monocular video of one person into consistent multiview videos for downstream 4D Gaussian Splatting reconstruction. It is an open-source project on GitHub: https://github.com/ant-research/4DAnyone.

Who is 4DAnyone for?

Built for researchers and developers with an NVIDIA GPU who want to generate multiview videos of a person from a single phone or casual video.

What can I do with 4DAnyone?

3 use cases so far, for example: Turn a casual clip into a 24-view orbit set; Preview camera layouts in a browser GUI; Run a quick 6-view test on a consumer GPU. Each has steps and a copy-paste agent prompt.

What do I need to run 4DAnyone?

A CUDA-capable NVIDIA GPU (README cites peak use below 24 GB and an RTX 4090 benchmark); Git and conda installed; A source video that is a single person, 1080p or higher, 9:16 portrait, at least 121 frames; Permission to use the person shown in the source video.

What are alternatives to 4DAnyone?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is 4DAnyone safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.