LTX2.3 Graphic and video workflow｜Image reference Text control 10S similarity maintenance full process

This workflow is an image-to-video generation system built on LTX2.3 Dev-Dare TIES Distilled 1.1 + Image Reference + PromptRelay Smart Text Control + Third-Order Image Constraints + 10S Similarity Maintenance + Third-Order Sampling HD Refinement. After users upload a reference image and text prompts, the system can generate short videos while ensuring consistency in the reference subject, actions, and style.

Core Process Description:

1. Image Reference for Subject Locking: The reference image uploaded by the user undergoes image scaling and preprocessing before entering the initial constraint stage of video generation. This step ensures that the subject's identity, hairstyle, clothing, and background in the video remain consistent with the reference image.
2. Global Prompt Control: Users input global prompts to define overall visual rules, such as character identity, scene environment, art style, lighting effects, and camera rules. Global prompts participate in the third-order generation to ensure a unified overall style of the video visuals.
3. Segmented Prompt Control for Actions: Segmented prompts can refine the actions, expressions, and camera changes of each time period. For example, the character smiles in the first 2 seconds, slightly turns their head from 3 to 5 seconds, and finishes the action from 6 to 10 seconds. The system generates the continuity of each frame's action based on these prompts.
4. Audio and Video Synchronization (Optional): If additional audio is used as a reference, the system extracts the audio latent space to ensure lip-sync and action synchronization.
5. 10S Similarity Maintenance: Through the newly added similarity maintenance system, including face detection, similarity guidance, anchor perception, and STG advanced guidance, it ensures that the character does not deviate from the reference image throughout the video, actions are natural, and high-recognition identity consistency is maintained.
6. Third-Order Sampling HD Refinement: After third-order sampling, the video generates HD refined results, ensuring exquisite details, clear image quality, no messy particles, or excessive sharpening.

Applicable Scenarios:

• AI short dramas and character storyboards: Quickly generate short storyboard animations from static reference images
• Character talking-head/singing videos: Single digital human performing talking-head or songs
• Commercial product display: Dynamic presentation of product reference images
• Game concept videos or IP character performances: Generate dynamic scenes referencing concept art
• Social media assets: Dynamic covers or short clips for platforms like Xiaohongshu, Bilibili, Douyin, etc.
• RunningHub Application scenarios: Provides beginner users with one-click image-to-video generation functionality

Core Advantages:

• High Fidelity: High maintenance of the reference image subject and character identity
• Natural Actions: Segmented prompts control coherent character actions and expressions
• HD Video: Third-order sampling refinement output, clear details, and stable image quality
• Simple Operation: Simply upload a reference image and enter prompts to generate short videos
• Fast Reproducibility: Random seed can be fixed to ensure consistent results
• Strong Applicability: Can be used in multiple scenarios such as entertainment, business, education, and content creation

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