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Create seamless transitions with LTX 2.3

Create seamless transitions between shots with this LTX 2.3 workflow, featuring the FLW LoRA from Systsms

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Input

A soundtrack for the whole result. The LoRA works best with audio; it is kept as is.

  • 0:00 / 0:00

The clip the transition starts from; its last loaded frames lead into the transition.

The clip the transition ends on.

Length of the result at 24 fps (97 is about 4 s). Transition length = total minus the frames from each shot.

Output width; the height follows Shot A's proportions.

Advanced settings

How many frames of Shot A open the result.

Default: 25

How many frames of Shot B close the result.

Default: 25

Leave empty for a new result each run. Enter a number to repeat one.

Frames to skip at the start of Shot A.

Default: 20

Frames to skip at the start of Shot B.

Default: 65

Distilled LTX 2.3: 8 steps is the default.

Default: 8

Run

Output
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Example

试试一个示例

关于此工作流

This ComfyUI workflow builds seamless, text-guided transitions between two source clips using the LTX 2.3 video diffusion model and the SYSTMS FLW transition LoRA. The MODELS group loads the transformer-only LTX 2.3 backbone via DiffusionModelLoaderKJ, the matching VAE with VAELoaderKJ, and applies the FLW LoRA using LoraLoaderModelOnly to bias the model toward natural, flow-like shot changes. Prompts are encoded with CLIPTextEncode (optionally auto-generated by a Gemini node), then routed through LTXVConditioning and LTXVAddGuide to steer the transition content and style.

Under the hood, the workflow allocates a timeline in EmptyLTXVLatentVideo, manages A/V latent streams with LTXVSeparateAVLatent and LTXVConcatAVLatent, and localizes denoising to the handoff region using SolidMask and SetLatentNoiseMask. Sampling is handled by SamplerCustomAdvanced with CFGGuider, KSamplerSelect, BasicScheduler, and RandomNoise for reproducibility.

After inference, VAEDecode reconstructs frames and VHS_VideoCombine assembles them into a final video. LTXVCropGuides provides compositional guides to keep subjects aligned between shots, helping the model generate cleaner, more believable morphs.

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