| --- |
| base_model: |
| - Lightricks/LTX-2.3 |
| tags: |
| - video-generation |
| - lora |
| - ic-lora |
| - ltx-video |
| - camera-motion |
| - lightricks |
| widget: |
| - text: >- |
| point-of-view of a spaceship flying above an asteroid while chasing an |
| X-Wing spaceship, firing green laser beams |
| output: |
| url: assets/test-compa_00007.mp4 |
| - text: >- |
| woman walks on a rainy street. the camera zooms out and upwards showing the |
| city around |
| output: |
| url: assets/test-compa_00016.mp4 |
| - text: girl is sitting on the bed while the camera pans left |
| output: |
| url: assets/test-compa_00001.mp4 |
| - text: woman walking with blowing magical halo behind her head |
| output: |
| url: assets/test-compa_00012.mp4 |
| - text: woman casting magic orbs with her hands |
| output: |
| url: assets/test-compa_00011.mp4 |
| - text: woman in black armor stands still and starts to salute |
| output: |
| url: assets/test-compa_00009.mp4 |
| - text: woman sitting on the bed holding a smoking gun |
| output: |
| url: assets/test-compa_00013.mp4 |
| - text: ballerina walks slowly |
| output: |
| url: assets/test-compa_00008.mp4 |
| - text: woman is walking across the room |
| output: |
| url: assets/test-compa_00015.mp4 |
| - text: woman standing in a narrow storage room |
| output: |
| url: assets/test-compa_00014.mp4 |
| - text: '""' |
| output: |
| url: assets/test-compa_00002.mp4 |
| - text: '""' |
| output: |
| url: assets/test-compa_00003.mp4 |
| --- |
| |
| # LTX-Video 2.3 22B — IC-LoRA: Cameraman v2 |
|
|
| A fine-tuned In-Context LoRA (IC-LoRA) adapter for LTX-Video 2.3 (22B), |
| trained to replicate camera movements from a reference video. |
|
|
| This is **v2** of the [Cameraman IC-LoRA](https://huggingface.co/Cseti/LTX2.3-22B_IC-LoRA-Cameraman_v1) with |
| a larger and more diverse dataset. |
|
|
| ## Example outputs |
|
|
| Each video shows the reference (camera-motion input) and the generated output. |
|
|
| <Gallery /> |
|
|
| ## Usage (ComfyUI) |
|
|
| I tested this lora only in **ComfyUI**. An example workflow is here: |
| https://huggingface.co/datasets/Cseti/ComfyUI-Workflows/blob/main/ltx/2.3/ic-lora-cameraman-v2/README.md |
|
|
| How it works: |
| - Load `LTX2.3-22B_IC-LoRA-Cameraman_v2_14000.safetensors` as the LoRA. |
| - Provide a **reference video** carrying the camera motion you want to replicate. |
| - Provide a **starting image**. This is optional. The model works both in T2V or I2V mode. |
| - Provide a **text prompt** describing the scene to generate. |
| - No trigger word is needed. |
|
|
| ## Tips |
|
|
| - **Resolution:** based on my testing, the higher the resolution, the more closely |
| the reference camera motion is followed. I wouldn't go below **960x512** for the first pass. |
| - **Image (conditioning) strength:** use an image strength of **0.5 or 0.7** for more motion. |
| - **The prompt matters a lot** — it strongly affects the camera movement. If the output |
| doesn't follow the reference camera motion, you can try: |
| - leaving the prompt empty (in some cases this works best), |
| - a different seed, |
| - describing the camera motion explicitly, at least at a high level. |
|
|
| ## Training Details |
|
|
| This IC-LoRA was trained on [RunPod cloud GPUs](https://runpod.io?ref=vpp0cion) |
| (NVIDIA RTX PRO 6000 Blackwell, 96 GB). |
|
|
| | Parameter | Value | |
| |---|---| |
| | Base model | LTX-Video 2.3 (22B) | |
| | Training framework | ltx-trainer (Lightricks) | |
| | Training strategy | IC-LoRA (video_to_video) | |
| | Released checkpoint | step 14,000 | |
| | LoRA rank / alpha | 64 / 64 | |
| | Target modules | attn1, attn2 (to_k/q/v/out), ff.net.0.proj, ff.net.2 | |
| | Optimizer | ProdigyPlusScheduleFree (auto-LR, prodigy_steps 1000) | |
| | Scheduler | constant (required by schedule-free) | |
| | Mixed precision | bf16 | |
| | Batch size | 1 (gradient checkpointing enabled) | |
| | Training dataset | 343 video pairs (+ 23 held-out for validation loss) | |
| | Resolution buckets | 768x512x{57,89,113,121} @ 24fps | |
| | First frame conditioning | 0.3 | |
|
|
| ### Dataset |
|
|
| 366 curated reference/target pairs (343 train / 23 held-out validation, 0 overlap). The set covers |
| single-axis motions as well as many compound multi-axis combinations |
| (e.g. pan_left + tilt_up + roll_ccw, dolly_in + truck_left + pedestal_down). |
|
|
| Motion-component frequency across the training set (a pair can contribute to |
| several components): |
|
|
| | Component | Count | |
| |---|---| |
| | pan_right | 93 | |
| | pan_left | 90 | |
| | dolly_in | 83 | |
| | roll_cw | 79 | |
| | truck_right | 79 | |
| | roll_ccw | 77 | |
| | tilt_up | 75 | |
| | zoom_in | 69 | |
| | truck_left | 68 | |
| | tilt_down | 62 | |
| | dolly_out | 61 | |
| | zoom_out | 52 | |
| | pedestal_down | 50 | |
| | static | 28 | |
| | pedestal_up | 25 | |
|
|
| Of the 343 training pairs, 93 are single-axis and 250 are compound (multi-axis). |
|
|
| ## Limitations |
|
|
| - Complex compound motions may not transfer reliably |
|
|
| ## License |
|
|
| This LoRA is created as part of a personal |
| project for research purposes only and is not intended for commercial use. |
|
|
| ## 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: |
|
|
| [](https://ko-fi.com/chetyart) [](https://liberapay.com/chetyart/donate) |
