LTX-Video 2.3 22B — IC-LoRA: Cameraman v1

A fine-tuned In-Context LoRA (IC-LoRA) adapter for LTX-Video 2.3 (22B),

trained to replicate camera movements from a reference video.

Example ComfyUI workflow

You can find a ComfyUI workflow example here: https://huggingface.co/datasets/Cseti/ComfyUI-Workflows/blob/main/ltx/2.3/ic-lora-cameraman/README.md

Example outputs

Each video shows the reference (left) and generated output (right) side by side.

How It Works

During inference you provide:

A reference video that carries the desired camera motion
A text prompt describing the scene to generate

The model transfers the camera behavior from the reference into the generated

output. No trigger word is required.

Training Details

This IC-LoRA was trained on RunPod cloud GPUs.

| Parameter | Value |

|---|---|

| Base model | LTX-Video 2.3 (22B) |

| Training framework | ltx-trainer (Lightricks) |

| Training strategy | IC-LoRA (video_to_video) |

| Best checkpoint | step 10,500 |

| LoRA rank / alpha | 32 / 32 |

| Target modules | attn1, attn2 (to_k/q/v/out), ff.net.0.proj, ff.net.2 |

| Learning rate | 1e-4 (linear decay) |

| Mixed precision | bf16 |

| Batch size | 1 (gradient checkpointing enabled) |

| Training dataset | 77 video pairs |

| Resolution buckets | 768x512x57; 768x512x89; 768x512x121 |

| First frame conditioning | 0.2 |

Dataset

77 video pairs annotated by camera motion type, balanced to up to 15 samples

per motion component. Some compound motions (e.g. zoom_in + tilt_up, orbit_cw + pan_left) are also represented.

| Motion | Samples |

|---|---|

| zoom_in | 15 |

| zoom_out | 15 |

| tilt_up | 15 |

| tilt_down | 9 |

| pan_left | 15 |

| pan_right | 15 |

| orbit_cw | 15 |

| orbit_ccw | 15 |

Usage

Requires the ltx-trainer repo and its dependencies.

uv run python -m ltx_pipelines.ic_lora \
    --distilled-checkpoint-path /path/to/ltx-2.3-22b-distilled.safetensors \
    --spatial-upsampler-path /path/to/spatial_upsampler.safetensors \
    --gemma-root /path/to/gemma \
    --lora lora_weights_step_10500.safetensors 0.8 \
    --video-conditioning /path/to/reference.mp4 1.0 \
    --prompt "Your scene description here" \
    --width 768 --height 512 --num-frames 97 \
    --output-path output.mp4

--video-conditioning: reference video carrying the camera motion to replicate, followed by conditioning strength
--lora: path to this LoRA followed by strength (0.7–1.0 recommended)
No trigger word needed

Tips

If the camera motion transfer feels too subtle, explicitly describe the desired

movement in the prompt. This can strengthen the effect.

Limitations

First experimental IC-LoRA checkpoint — results may vary
Complex compound motions may not transfer reliably
Only tested with I2V (image-to-video) conditioning — T2V mode is untested

License

Apache 2.0

Support

Producing and sharing this kind of open-source work requires renting cloud GPUs, which gets expensive quickly. If you find it useful and would like me to keep contributing, your support is very much appreciated:

![Ko-fi](https://ko-fi.com/chetyart) ![Liberapay](https://liberapay.com/chetyart/donate)

Cseti/LTX2.3-22B_IC-LoRA-Cameraman_v1