shim0114/T2V-Diffusion-Search
[NeurIPS 2025] Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search
This helps researchers improve the quality of text-to-video generation, making the generated videos better match the input text description. It takes a text prompt and an existing video generation model, and produces a higher-quality video output. This tool is for AI researchers or machine learning engineers focused on advancing text-to-video capabilities.
Use this if you are a researcher working with text-to-video generation models like Latte, CogVideoX, or Wan 2.1 and want to enhance the alignment between your input text and the resulting video.
Not ideal if you are looking for an end-user application to generate videos without deep technical setup, as this requires familiarity with machine learning environments and model configurations.
Stars
14
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 24, 2026
Commits (30d)
0
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