Descriptions:
This tutorial from the Veteran AI channel provides a thorough practical guide to video inpainting with the LTX 2.3 model, covering character replacement, reference-image-guided generation, and facial restoration in a single ComfyUI workflow. The video targets creators who want precise local edits to video — swapping out a character’s appearance while preserving background and motion — and addresses the specific failure modes that make this harder than it looks.
The workflow combines the LTX 2.3 inpaint LoRA (Kijai’s build, rank 128, 2,500 training steps) with SAM 3.1 for automated subject tracking and masking across all frames, all running on the RunningHub online ComfyUI platform. The instructor explains the LTXV Add Guide Multi node from KJnodes in detail, covering how to pass control video, latent inputs, and encoded prompts to steer generation. A key principle emphasized throughout is mask preparation: expanding and blockifying the mask so the model can clearly identify the shape being replaced, rather than guessing — a step the presenter demonstrates causes significant quality degradation when skipped.
The tutorial also covers a reference-image technique that gives creators direct control over the appearance of the replacement character, bypassing the otherwise random output of standard inpainting. Prompt writing strategy (describe the full scene, not just the masked region), LoRA chaining order, and two-stage sampling (base generation plus upscaling) are all addressed. The presenter also gives an honest assessment of remaining limitations, noting that character consistency during turns remains an unsolved problem in current video generation models.
📺 Source: Veteran AI · Published May 17, 2026
🏷️ Format: Tutorial Demo
