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: