Community Collaboration Enhancement Program
As an open source project, Step-Video-T2V specifically encourages community contributions to extend its scene adaptation capabilities:
- Data set contribution: Upload labeled domain-specific video clips (medical/educational/industrial, etc.) in 16×16 compressed format.
- Model Tuning: Fine-tuning on specialized domain data using the provided train.py script, submitting Pull Requests
- Plug-in Development: Develop export adapters for Blender/UE and other 3D software.
Specific pathways to participation:
- Create feature branch after Fork project (naming convention: feature/scene name)
- Following the code specification of CONTRIBUTING.md
- Verify performance impact using the provided test_benchmark.py before committing
Outstanding contributions will be awarded:
- Incorporation of official model branches
- Gaining Arithmetic Support from Step Star
- Priority access to new features
The current scenes that need to be optimized urgently include: microscopic photography, ancient style animation, sports events and other professional fields.
This answer comes from the articleStep-Video-T2V: A Vincennes Video Model Supporting Multilingual Input and Long Video GenerationThe
May not be reproduced without permission:AI productivity tools " How can community contributions enhance Step-Video-T2V's scene-specific generation capabilities?
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