---
license: apache-2.0
base_model: Lightricks/LTX-2.3-22B
library_name: diffusers
---

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

**Proof-of-concept** IC-LoRA adapter for [Lightricks/LTX-2.3-22B](https://huggingface.co/Lightricks) 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 v0.2 with a much larger, more diverse
> dataset is planned.

---

## 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)
- **1024×512 @ 24 fps, 41 frames** at inference

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

## Usage

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

- **Trigger word**: `equirectangular` (required, include in every prompt)
- **Reference video**: your source clip projected into the equirect canvas with unknown regions masked
- **Resolution**: 1024×512, 41 frames, 24 fps (other shapes untested)

Recommended starting points:

- LoRA strength: **1.0**
- Guidance scale (CFG): **4.0**
- STG scale: **1.0**, blocks `[29]`, mode `stg_v`
- Inference steps: **20–30**

### Companion tooling

A small ComfyUI helper node — **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.

## Training (v0.1)

| | |
|--|--|
| Base model | LTX-2.3-22B (dev) |
| Strategy | IC-LoRA (`video_to_video`) |
| Rank / alpha | 128 / 128 |
| Target modules | video self+cross attention + FFN |
| Resolution | 1024×512, 41 frames @ 24 fps |
| Optimizer | Prodigy (D-Adaptation), lr=1.0, constant |
| Precision | bf16, gradient checkpointing |
| Steps | 3500 |
| Hardware | 1× NVIDIA H100 80GB |
| Dataset | Small curated POC set (not released) — semi-static city establishing clips |

Multiple checkpoints are published so you can pick the one that best fits your content:
`step_00500`, `step_01500`, `step_02700`, `step_03500`.

## What's next (v0.2)

v0.2 is planned on a significantly larger and more diverse dataset (thousands of clips) 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

## License

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