Seedance 2.0 clips come out of Xiaoyunque with a corner watermark and a modest frame rate. This episode chains two ComfyUI graphs to fix both: a MiniMax remover built on the early Wan 2.1 work to take the watermark out by masking it, then a GIMM interpolation pass and a FlashVSR upscale. The author reports the watermark is "almost gone" and the upscaled result reaches roughly 2K after a 960-pixel constraint.

Evidence note: parameters below were parsed from the workflow JSON shipped with this episode (2 files); anything the video reports about results is attributed to the author.

When this is useful

  • You generate clips yourself and want them clean and high-frame-rate before editing.
  • Your delivery target wants 32 or 60 fps from a 16 fps source.
  • You need a repeatable post chain instead of a one-off manual fix.

Two graphs, two jobs

Watermark removal

Load the video. If your clip did not come from Xiaoyunque and the watermark is not in the bottom-right, run the graph once while keeping the first frame, then paint the mask on that frozen frame - the author also paints the top-left when the mark is there.

Constrain the size, then write a prompt describing what is under the mask. The graph masks the watermark area in grey and lets the model inpaint it.

The model is MiniMax's early video watermark remover built on Wan 2.1. It is self-accelerating; the author adds a LightX2V accelerator as insurance for better results.

Interpolation, then upscale

The second graph is a straight line: load the source, set the interpolation multiplier, set the upscale multiplier, run.

The author's settings: 2x interpolation with the source locked at 16 fps (so 32 fps out) and 3x upscale after a 960-pixel size constraint, which lands close to 2K.

Frame interpolation first, upscale second - the author does not reverse that order.

Where the clips come from

The source is Xiaoyunque's web app (a Jianying/CapCut platform), using Seedance 2.0 in "immersive short film" mode. You upload references with the plus button and can address them as @图1, @图2 in the prompt, which the author notes also sidesteps some input restrictions.

Daily login gives one free clip of up to 15 seconds; each invited friend brings 188 credits, capped at three. Face reference is flagged as not yet supported in this mode.

The 'ComfyUI is dying' argument

The episode closes on the community worry that hosted models make local workflows pointless. The author's answer is narrow and reasonable: open tooling runs offline, has no queue and no content ceiling, and stays useful as the component you use when you need a specific adjustment rather than a whole clip.

How to run it

  1. Open the watermark-removal graph and load the clip.
  2. If the watermark is not bottom-right, keep the first frame and paint the mask over the mark on that frame.
  3. Constrain the output size and prompt what should appear where the watermark was.
  4. Run; the MiniMax remover inpaints the masked region.
  5. Open the interpolation + upscale graph, load the cleaned clip, set 2x interpolation and 3x upscale, with the size constraint at 960 px.
  6. Render and check for interpolation artifacts on fast motion.

Parameter basis

minimax remover 视频去水印 - 26 nodes

No UNET/CLIP/VAE sampler chain in this graph - it is a processing or composite graph. Node inventory: MaskToImage, WanVideoEncode, PreviewImage, VHS_VideoCombine, WanVideoMiniMaxRemoverEmbeds, LoadWanVideoT5TextEncoder, GrowMaskWithBlur, WanVideoVAELoader (26 nodes).

视频补帧+放大 - 7 nodes

No UNET/CLIP/VAE sampler chain in this graph - it is a processing or composite graph. Node inventory: GIMMVFI_interpolate, LayerUtility: ImageScaleByAspectRatio V2, DownloadAndLoadGIMMVFIModel, FlashVSRNode, VHS_LoadVideo, PreviewImage, VHS_VideoCombine (7 nodes).

These are video-processing graphs: there is no UNET, CLIP, VAE or KSampler to quote. The only numeric settings are the ones in the node widgets (interpolation multiplier, upscale multiplier, 960-pixel constraint), which the video states and the JSON carries.

Honest limits

  • The remover needs a mask. It works when you tell it where the watermark is; it is not a blind detector.
  • The model is an early MiniMax/Wan 2.1 build, not a purpose-trained 2026 remover.
  • Interpolation cannot invent detail: very fast or occluded motion will smear.
  • Xiaoyunque's free quota (one clip per day, 15 s) and the missing face reference limit what you can source.
  • Removing watermarks is only appropriate on footage you own or are licensed to process - the tool has no rights model.

Episode resources