VR-360-Outpaint-LTX2.3-IC-LoRA

LTX-2.3 — 360° Equirectangular Outpainting IC-LoRA · v0.1

Proof-of-concept IC-LoRA adapter for Lightricks/LTX-2.3-22B that outpaints standard widescreen footage into a full 360° equirectangular projection for immersive/VR viewing.

This is an early v0.1 release. Expect rough edges, limited subject variety, and inconsistent coherence outside the sweet spot described below. A new version with a much larger, more diverse dataset is planned.

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Samples

Three clips from the model. sweep is a rendered 2D camera pan through the 360° output — the easiest way to judge results without a VR player. fl-eq shows the flat source and the equirect output side-by-side.

Clip 1 — sweep

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip1-sweep.mp4"></video>

Side-by-side (flat input · equirect output):

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip1-fl-eq.mp4"></video>

Clip 2 — sweep

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip2-sweep.mp4"></video>

Side-by-side:

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip2-fl-eq.mp4"></video>

Clip 3 — sweep

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip3-sweep.mp4"></video>

Side-by-side:

<video controls loop muted playsinline src="https://huggingface.co/TheBurgstall/VR-360-Outpaint-LTX2.3-IC-LoRA/resolve/main/samples/clip3-fl-eq.mp4"></video>

Raw equirectangular outputs (load in a 360° player for VR): clip1-eq.mp4 · clip2-eq.mp4 · clip3-eq.mp4

What it does

• Input: a flat 2.39:1 (cinemascope) clip and a matching equirectangular reference (the input projected into the equirect canvas, with the unknown regions left masked/black)
• Output: the model fills in the masked regions, turning the flat shot into a plausible 360° equirectangular video that can be viewed in a VR/360 player

Intended for transforming existing live-action or cinematic footage into immersive content.

Sweet spot (v0.1)

The v0.1 model was tuned toward a deliberately narrow domain to validate the approach:

• Semi-static establishing city / urban scenes (no heavy camera motion)
• ~100° horizontal field of view in the source clip
• 2.39:1 source aspect (standard cinemascope)

It will generalize poorly outside these conditions — fast action, extreme close-ups, heavily stylised imagery, or very different FOVs are not reliably handled yet.

Files

Three sample clips (clip1, clip2, clip3) are included under samples/.

Usage

Load on top of ltx-2.3-22b-dev.safetensors with the LTX-2 video_to_video pipeline and pass:

• Trigger word: equirectangular (works without any trigger word or prompt too, but with a descriptive prompt you can direct the content of outpainted part)
• Reference video: your source clip projected into the equirect canvas with unknown regions masked
• Resolution: 1920x960, 121 frames, 24 fps

Only tested in ComfyUI with the workflow available in this repo. Please note that the workflow's padding node crops your input footage to 2.39:1, you can select whether it's cut from center, top or bottom. Other aspect ratios will work poorly in this early version.

Companion tooling

A small ComfyUI helper pack — ComfyUI-EquirectProjector — was written alongside this LoRA to produce the masked equirectangular reference from a flat clip. Pair it with the standard LTX-2 video-to-video nodes. The Equirect-Outpaint.json workflow in this repo shows the exact wiring.

Training (v0.1)

The final step 3500 checkpoint is shipped here. Intermediate checkpoints were used for validation during training but aren't included in this release.

What's next

Next version is planned on a significantly larger and more diverse dataset covering:

• Broader subject matter (interiors, landscapes, crowds, vehicles, …)
• Varied input FOVs and focal lengths
• A wider range of camera motion — not just static establishing shots
• Better handling of the polar regions (top/bottom caps of the equirect canvas)

Limitations

• Does not model the top/bottom caps of the sphere well — expect stretching or repetition
• Struggles with busy motion and fast cuts
• Prompt adherence is weak; conditioning is dominated by the reference video
• Outputs are not a substitute for natively captured 360 footage — this is a creative re-projection, not a reconstruction

Acknowledgements

• First part of the training done at ADOS Paris event in collaboration with Cseti (https://huggingface.co/Cseti), NebSH (https://huggingface.co/Nebsh) and S4f3ty_Marc (https://huggingface.co/s4f3tymarc). Good times, thank you guys.
• Advice from oumoumad (https://huggingface.co/oumoumad) in IC-LoRA training altogether has been very valuable to me. The workflow included in this release is modified from oumoumad's IC-LoRA workflow.

License

Apache-2.0. Inherits any base-model conditions from LTX-2.3-22B.