

Long Context Tuning (LCT)
Overview :
Long Context Tuning (LCT) aims to bridge the gap between current single-generation capabilities and real-world narrative video production. This technology directly learns scene-level consistency through data-driven methods, supporting interactive multi-shot development and synthetic generation, applicable to all aspects of video production.
Target Users :
This technology is suitable for video producers, directors, and creative professionals, helping them achieve greater flexibility and creativity in video creation. Its real-time feedback mechanism allows creators to iterate quickly and improve production efficiency.
Use Cases
Produce a complete narrative video in a short time.
Synthesize a smooth video from different character and environmental images.
Quickly expand content based on existing video materials.
Features
Enhanced Scene-Level Video Generation: Improves the consistency and coherence of video generation by expanding the context window.
Interactive Multi-Shot Development: Allows users to iteratively adjust based on previously generated content with real-time feedback.
Seamless Single-Shot Extension: Extends a single shot to several minutes while maintaining visual consistency.
Synthetic Generation: Accepts different identity and environmental images to generate a consistent video that blends these elements.
Unified Visual Conditioning: Asynchronous training strategy allows the use of any image or video as additional conditioning.
Wide Applicability: Excels in generating human-centric content and various fields such as nature documentaries.
How to Use
Select the desired video type, such as a narrative video or documentary.
Provide initial text prompts or images to guide the generation process.
Use the interactive interface for real-time adjustments and observe the generation results.
Input new prompts or modify existing prompts as needed during the generation process.
After completion, export the generated video for sharing or further editing.
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