CrossView-Warp lora workflow for Minimax H3
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README.md
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---
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## LTX Video 2.3
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| Workflow | Description | Type | Updated |
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---
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## MiniMax H3
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| Workflow | Description | Type | Updated |
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|---|---|---|---|
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| [CrossView Warp](https://huggingface.co/datasets/Cseti/ComfyUI-Workflows/blob/main/minimax-h3/crossview-warp/README.md) | V2V new-camera-angle LoRA — MoGe-2 geometry warp as an aligned guide, source clip as a Ref2VA reference, two-pass with audio (step 3.5k) | Video gen | 2026-09-20 |
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---
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## LTX Video 2.3
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| Workflow | Description | Type | Updated |
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minimax-h3/crossview-warp/README.md
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# MiniMax-H3 CrossView Warp — Video-to-Video new camera angle
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Takes a video and a camera offset and regenerates the same scene from that new
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viewpoint, with audio. MoGe-2 estimates metric depth, the CrossView Warp node
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reprojects the clip into the requested camera pose, and a custom-trained LoRA on
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MiniMax-H3 fills the disocclusion holes and completes the view. The warp carries
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the geometry and the original clip carries identity and appearance, so the two are
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fed to the model in different roles: the warp as an aligned guide, the source as an
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ordinary Ref2VA reference. Two-pass, base generation followed by a refinement pass.
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## Preview
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[preview.mp4](media/preview.mp4)
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## Requirements
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- ComfyUI with native MiniMax-H3 support (`MiniMax H3 Add Guide`, `MiniMax H3 Reference To Video`)
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- Custom node: [ComfyUI-CrossViewWarp](https://github.com/cseti007/ComfyUI-CrossViewWarp) — includes a walkthrough video for the camera controls
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- Custom node: [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes) — resize, labels, image range
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- Models:
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- [MiniMax-H3](https://huggingface.co/MiniMaxAI/MiniMax-H3) — ref2va transformer, Qwen3-VL text encoder, video VAE, audio VAE
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- [MiniMax-H3 CrossView Warp LoRA](https://huggingface.co/Cseti/MiniMax-H3_Ref2VA-LoRA-CrossView-Warp_v1)
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- MiniMax-H3 DMD 8-step turbo LoRA
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- MoGe-2 ViT-L (`moge_2_vitl_normal_fp16.safetensors`)
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## Notes
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- **Frame count must be 17k+5** — 73, 90, 107, 124, 141. Anything else is rejected or snapped.
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- **Resize the warp and the source to the same size** before the guide and reference nodes.
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- **Leave `pivot_override` off.** The node then estimates the orbit centre from MoGe's
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metric geometry. Hand-entered `pivot_z` values are the fastest way to destroy the warp:
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on a wide shot a wrong pivot gave 84% disocclusion with the subject gone, where auto
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pivot at the same angle gave 52% with everything intact.
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- **Prompt is one word: `crossview`.** The LoRA was trained with that single caption and
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no scene description.
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- LoRA strength 0.8, `res_multistep`, 8 steps with the turbo LoRA, sigma shift 12 video / 3 audio.
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- Angle range: azimuth up to +-90 is covered by the training data, elevation -20 to +30.
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Looking up from below is the weak direction. Distance is not followed reliably, leave it at 1.0.
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- Wide shots with strong foreground are the hard case: if the subject is far and something
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sits close to the lens, the camera move shreds the near field.
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- Output paths in the workflow are relative (`crossview_warp/...`), set them to your own.
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## Changelog
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- `2026-09-20` — initial release, LoRA step 3500
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minimax-h3/crossview-warp/crossview-warp-h3.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:87882facdfee8a8a58b6abb82222530f45d11b32f951a33f95ae16fb9ae74994
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size 126336
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minimax-h3/crossview-warp/media/preview.jpg
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Git LFS Details
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minimax-h3/crossview-warp/media/preview.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd54acbec806dbc1fab4b805ff243d07d9e7c388b754cca0fc90f873d7940d26
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size 9978964
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