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Wan2.2 Fun and RealismBoost LoRA for V2V

1.3k

Generates in about 5 mins 5 secs

Nodes & Models

Note
MarkdownNote
Fast Groups Bypasser (rgthree)
VAELoader
wan_2.1_vae.safetensors
CLIPLoader
umt5_xxl_fp16.safetensors
UNETLoader
wan2.2_t2v_low_noise_14B_fp8_scaled.safetensors
CLIPTextEncode
TorchCompileModel
Reroute
VAEEncode
LoraLoaderModelOnly
4steps-lora-250928-low_noise_model.safetensors
Wan14B_RealismBoost.safetensors
Wan2.2-Fun-A14B-InP-low-noise-HPS2.1.safetensors
ModelSamplingSD3
ContextWindowsManual
KSampler
VAEDecode
INTConstant
INTConstant
ImageResizeKJv2
PathchSageAttentionKJ
WanVideoEnhanceAVideoKJ
ImageConcanate
VHS_LoadVideo
VHS_VideoInfoLoaded
VHS_VideoCombine
ImageResizeKJv2
ImageConcanate
easy cleanGpuUsed

Video Detail Enhancer is an advanced workflow powered by the Wan2.2 Fun model and RealismBoost LoRA, designed to fix common issues in AI-generated videos such as blurry faces, hands, and textures, while dramatically upgrading the realism, sharpness, and consistency of animated content. By combining the superior Mixture-of-Experts (MoE) architecture of Wan2.2 Fun with a second-pass video-to-video (V2V) refinement workflow and the precision guidance of RealismBoost LoRA, this solution turns “average” AI video outputs into professional-grade cinematic sequences.

What is RealismBoost LoRA?

RealismBoost LoRA is a LoRA fine-tune specifically trained to correct facial and hand artifacts, enhance eye gleam, mouth expressions, and micro-details lost in most fast synthesis pipelines.

Use Cases

  • Anime, influencer, or character animation with clean identity, clear expressions, and detailed motion.

  • Marketing/product videos needing high-fidelity visuals and smooth transitions.

  • Film, storyboard, and music video concept prototyping with camera moves and scene progression.

  • Social media content that stands out with professional polish on both facial features and background elements.

Read more

N
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gaga82
2 months ago
this workflow is wrong its for z-image not wan!! fix it

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