IAMCCS CineInfo V2V Pose Transfer

IAMCCS CineInfo V2V Pose Transfer is one of those nodes that looks useless until you see the workflow it belongs to. By itself it just reads a cine_linx and prints a bunch of values. In the IAMCCS Shotboard V2V pipeline it's the thing that turns "shot three of the scene" into an actual FLUX Klein pose-transfer job: the right driving video, the right reference, the right resolution, prompts already filled in.

Here's the honest framing up front: this is an orchestration node for the author's own multi-shot V2V production system, not a drop-in utility. If you're building a pose-transfer workflow from scratch, you don't need it. If you're loading an IAMCCS V2V workflow (they're posted on r/comfyui by the author and distributed through his Patreon), this is what unrolls each shot so the backend sampler can just run.

How it works

The pack's "Cine" layer is built on a bus called cine_linx - a JSON blob that carries the whole shot plan: source video, reference image, resolution, fps, global/negative prompts, output prefix, even the audio. CineInfo nodes read that payload and extract what a specific backend needs. This one targets the FLUX Klein Pose Transfer backend (the code's backend template calls it flux_klein_pose_transfer), which is the canvas-style mode: you drive a pose from a reference image and a driver video, and the pipeline produces a result image you can hand onward as a V2V reference.

It loads the source video via VHS, pulls the reference image, splits the source into the current segment (using the plan's segment math), normalizes the audio for LTX, and hands you everything ready to wire into a sampler chain.

The inputs and outputs that matter

Only one input is required:

• cine_linx - the plan bus. Everything else is derived from it.

The optional source_images, source_audio, and result_image let you override what the plan points at. result_image is the interesting one: it's where a previous pose-transfer pass' output gets fed back in.

Outputs worth actually wiring up:

• driver_video and reference_image - the two things your pose/control preprocessor wants.
• fps, generation_width, generation_height - feed these to your empty latent and sampler so every shot uses the plan's resolution.
• positive_prompt / negative_prompt - already assembled per shot.
• source_audio - keep this if you're doing lipsync or audio conditioning downstream.
• backend_profile, report - diagnostics telling you which backend path was selected and why.

How to install

This is one of 150+ nodes in IAMCCS-nodes, by IAMCCS (Carmine Cristallo Scalzi). The pack is on ComfyUI Manager:

1. Manager → "Install Custom Nodes" → search IAMCCS.
2. Restart ComfyUI.

Or manually:

cd ComfyUI/custom_nodes
git clone https://github.com/IAMCCS/IAMCCS-nodes.git

The README asks for ComfyUI ≥ 0.3.0, Python ≥ 3.12, and Torch ≥ 2.8. The Cine V2V path also assumes you have the standard LTX nodes, VideoHelperSuite for video load/combine, and the LTX audio-video model setup - see SUPERNODES_REQUIREMENTS.md in the repo for the full dependency matrix.

Where people get burned

• Nothing happens when you run it alone. It needs a real cine_linx from a Shotboard/V2V planner upstream. Blank cine_linx = defaults, which point at the author's local test files (IMG_4145 2.mp4…). Don't panic at that default filename; it just means no plan was attached.
• A second copy of IAMCCS-nodes in custom_nodes is the pack's classic footgun - the requirements doc calls it out explicitly. Duplicate folders → duplicate node registration → startup failures. Keep exactly one.
• Version mismatch. The Cine nodes land in v1.4.5+ (May 2026) and the V2V engine keeps moving. Old saved workflows with changed widget order can load with wrong dropdown values; re-add the node if something looks off.
• This is pre-release-feeling, one-author tooling with essentially no install base (zero search impressions on this page as of writing). The author is responsive on r/comfyui but there's no army of users to debug your graph. Be ready to read the report outputs.