SCAIL-2 In-Video Character Replacement (WAN 2.1)

SkillMedia

SCAIL-2 in-video character replacement on WAN 2.1. WanSCAILToVideo + SCAIL2ColoredMask + SAM3, the reference-image framing→scale rule, and the tuning/compositing pitfalls

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the SCAIL-2 In-Video Character Replacement (WAN 2.1) skill

What this skill tells your AI

The instructions your AI receives, as published by artokun/comfyui-mcp in plugin/skills/wan-scail-replacement/SKILL.md and read by ahel’s review.

SCAIL-2 (zai-org, on WAN 2.1 14B) replaces the person in a driving video with a character you supply as a reference image, end-to-end, with no pose maps, and with multi-character support. It is the successor to WAN Animate / motion transfer for the "swap the subject, keep the motion" job. The official ComfyUI template is video_wan21_scail2_character_replacement_int8, built around WanSCAILToVideo (+ SCAIL2ColoredMask) with a SAM3 mask driving where the character goes.

This skill documents the non-obvious behaviours that cost a full multi-minute render to discover. It is not a from-scratch graph. Start from the official template and apply the guidance below.

The one rule that costs a re-render: reference framing controls SCALE

In replacement_mode: true, the reference image's FRAMING controls the output character's SIZE as well as its appearance. The SAM3 mask controls where the character is placed; the reference image controls how large.

Measured on a 720x1280 driving clip where the subject occupied ~30% of frame height (subject bbox 363 px):

Reference framingPerson bbox in outputvs driving subject
Full-bleed portrait (person ~93% of frame)621 px1.71x oversized
Reframed (person ~34% of frame)364 px1.003x — correct

After reframing, top/bottom registration matched the driving subject within 1 px (the character stands on the same ground plane at the same height). Pose transfer was correct in both cases. Only the scale was wrong, which makes it easy to misread as "the model works" until you A/B against the source.

Guidance: pad or reframe the reference before you render.

Pad/reframe the reference image onto a canvas at the working resolution so the person occupies roughly the same fraction of frame height as the subject in the driving video. A full-bleed portrait reference against a wide-shot driving clip renders the character oversized in proportion to the framing mismatch.

It is a trap because the template's on-canvas notes do not state it, and it does not show up in the popular Civitai motion-transfer workflows. Those run animation mode, where the reference legitimately fills the frame.

Tuning trade-off: distill LoRA strength / shift leaks driving-subject detail

Running the lightx2v distill LoRA at 0.8 with ModelSamplingSD3 shift 5 (the settings the popular Civitai workflow uses) improves colour and detail versus 1.0 / shift 8. It also increases adherence to the driving video enough that original-subject details bleed onto the replacement character. In one run the original golfer's neon-yellow shoe appeared on a replacement character who wears white shoes in the reference (same seed, same reference, only those two params changed). If you see source details you didn't ask for, raise the LoRA strength / shift back toward 1.0 / shift 8.

Don't "fix" colour with post-hoc compositing — it's a regression

The raw SCAIL-2 output shows a measurable colour error (background ~-5 per channel from the VAE round-trip; the character loses red ~2.4x faster than green, which reads as a slight green cast). It is tempting to composite the generated character back over the original plate through the SAM3 mask to "correct" it. Don't. It measures better but looks worse:

  • The mask boundary produces an obvious halo.
  • Layering the original plate's props (e.g. a golf club) over generated hands severs the grip relationship the model had solved coherently.

SCAIL-2 resolves colour, edges, grip and occlusion jointly; correcting any one of them in isolation breaks the others. Leave the raw output alone.

Models (reference set)

The template's int8 build was exercised with:

  • wan2.1_14B_SCAIL_2_int8_convrot, the SCAIL-2 model
  • wan2.1_SCAIL_2_DPO_lora_bf16, the DPO LoRA
  • lightx2v_I2V_14B_480p_cfg_step_distill_rank64_bf16, the distill LoRA (see tuning note)
  • Wan2_1_VAE_bf16
  • umt5_xxl_fp8_e4m3fn_scaled, the text encoder
  • clip_vision_h
  • sam3.1_multiplex_fp16, the SAM3 mask model

VRAM: ~22.2 GB peak at 576x1024 / 81-frame chunks on a 24 GB card.

See also

  • wan-t2v-video, wan-flf-video for other WAN 2.x video pipelines
  • director for multi-shot scene direction for video pipelines

Sources

  • Official: none found.
  • Empirical: sampler values, wiring, and prompt notes from working graphs in packs/ and observed renders; not a vendor prompting guide.

Signals

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Sep 2026
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Source
github.com/artokun/comfyui-mcp