CIVITAI / Workflows

IC Edit Subtitle & Watermark Removal Video Cleanup Workflow

This workflow is designed for IC Edit-style subtitle and watermark removal, built on an LTX 2.3 video restoration pipeline. Its main purpose is to take an existing video with hardcoded subtitles, captions, random AI text, logo overlays, signatures, platform watermarks, or semi-transparent marks, and reconstruct a cleaner video result while preserving the original motion, subject identity, camera movement, lighting, and scene composition. Unlike a simple blur, crop, mosaic, or overlay method, this workflow uses a generative restoration approach. It does not just cover the unwanted text area. Instead, it uses LTX 2.3, subtitle-removal IC LoRA, watermark-removal IC LoRA, video frame extraction, prompt-guided reconstruction, latent inpainting-style processing, tiled VAE decoding, and final video recombination to rebuild the hidden background more naturally. The workflow uses ltx-2.3-22b-dev-dare-ties-distilled-1.1 as the main model route, with LTXVAudioVAELoader, CheckpointLoaderSimple, LTXAVTextEncoderLoader, LTXVConditioning, LTXAddVideoICLoRAGuide, LTXVImgToVideoConditionOnly, VAEEncodeForInpaint, SamplerCustomAdvanced, LTXVCropGuides, VAEDecodeTiled, VHS_LoadVideo, and VHS_VideoCombine. It also loads two dedicated IC LoRA models: ltx2.3-ic-subtitles-remove-general-lora and ltx2.3-ic-watermark-remove-general-lora. This makes the workflow focused on cleanup and reconstruction rather than ordinary image-to-video generation. The positive prompt is specifically written for removal tasks. It asks the model to remove subtitles, captions, hardcoded text, AI-generated garbled text, platform watermarks, logo overlays, signatures, and semi-transparent marks. At the same time, it asks the model to restore the underlying image using surrounding visual context while preserving facial features, body shape, object boundaries, lighting, texture continuity, camera motion, and scene composition. This is the correct logic for video cleanup: erase the unwanted layer, but do not destroy the original scene. The negative prompt suppresses common restoration failures such as blur, oversaturation, pixelation, low resolution, grain, distortion, noise, compression artifacts, JPEG artifacts, glitches, watermark, text, logo, signature, copyright marks, subtitles, distorted sound, saturated sound, and loud audio artifacts. This helps reduce the chance that the workflow removes one tex