CIVITAI / Workflows

LTX 2.3 Dual-Character Dialogue | Enhanced Cinematic I2V Workflow

This workflow is designed for LTX 2.3 dual-character dialogue video generation, focusing on stable two-person interaction, controlled left-right positioning, stronger motion continuity, and more polished final video quality. Its main purpose is to help creators turn a single reference image into a cinematic two-character conversation shot, where both characters remain visually consistent and the scene keeps a coherent dialogue rhythm instead of drifting into random motion. The workflow uses LTX 2.3 as the main video generation backbone, with ltx-2.3-22b-distilled-1.1 as the core checkpoint route. It also uses Gemma-style LTX text encoding, LTX audio VAE routing, LTX video VAE decoding, image-to-video conditioning, NAG enhancement, VBVR I2V LoRA support, latent upscaling, multi-stage sampling, and final video export. This makes it more advanced than a basic I2V workflow because it is built specifically for controlled character interaction rather than simple first-frame animation. The core strength of this workflow is two-character stability. In many AI video workflows, two-person scenes are difficult because characters may swap positions, merge into each other, lose identity, change clothing, or break the left-right relationship. This workflow is designed to reduce those problems by using the input image as a strong visual anchor, then reinforcing the generation with LTXVImgToVideoConditionOnly, LTXVConditioning, and a structured prompt. The negative prompt also directly suppresses subtitles, scene cuts, glitches, warping, extra limbs, extra hands, static frames, low-quality motion, and unwanted transitions. Another important feature is the VBVR I2V LoRA route. The workflow loads an LTX 2.3 VBVR I2V LoRA, which helps strengthen image-to-video behavior, motion consistency, and prompt adherence. This is especially useful for dialogue-style videos, where small gestures, facial direction, eye contact, and body positioning matter more than large chaotic movement. The workflow also includes NAG enhancement. NAG is used to improve guidance stability and reduce generation drift during sampling. For dual-character dialogue scenes, this matters because the video must preserve not only the scene style, but also the relationship between the two characters. The left character should remain on the left, the right character should remain on the right, and both should co