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    Human 360 Diffusion LoRA for FLUX.1-dev - v1.0
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    Overview

    This LoRA was trained with rank 64 on a diverse dataset of over 1000 images, for the purpose of creating 360 degree panorama images of humans.

    The seam and polar distortion artifacts should be minimal, but some careful editing or in-painting may be required to make the image appear seamless.

    Usage

    There is no trigger phrase, but as with all 360° Flux LoRAs, you should include some variation of '360 degree equirectangular view' in your prompt to improve output quality.

    When rendering images, it's recommended that you choose a 2:1 aspect ratio, like 1024x512, 1536x768, or 2048x1024. Afterwards, you can use an upscaler of your choosing to make the resolution high enough for skyboxes, VR, and 2D/3D environments.

    This model can also be used as the 'text to image' portion of 3D world workflows: Text to Image -> Image to Video -> Video to 3D World.

    Additional Tools

    HTML 360 Viewer

    To make the viewing and sharing of 360 images & video easier, I built a web browser based HTML 360 viewer that runs locally on your device.

    If you are a user of ComfyUI, then these sets of nodes can be useful for working with 360 images & videos.

    For Diffusers and other libraries, you can make use of the pytorch360convert library when working with 360 media.

    Limitations

    The dataset had a limited number of poses, and is geared towards North American and European depictions of humans.

    HuggingFace

    This model is also available for download on HuggingFace here (along with citation information): https://huggingface.co/ProGamerGov/human-360-lora-flux-dev

    Description

    FAQ

    LORA
    Flux.1 D

    Details

    Downloads
    139
    Platform
    CivitAI
    Platform Status
    Available
    Created
    8/23/2025
    Updated
    5/12/2026
    Deleted
    -

    Files

    human_360diffusion_lora_flux_dev_v1.safetensors

    Available On (1 platform)

    Same model published on other platforms. May have additional downloads or version variants.