Leaderboard for text-to-video generation models
Search for tagged characters in Animagine datasets
Browse and submit evaluation results for AI benchmarks
Generate a data profile report
Evaluate diversity in data sets to improve fairness
Generate detailed data reports
This project is a GUI for the gpustack/gguf-parser-go
Gather data from websites
Finance chatbot using vectara-agentic
Analyze data using Pandas Profiling
Display CLIP benchmark results for inference performance
Generate plots for GP and PFN posterior approximations
Generate benchmark plots for text generation models
VideoScore Leaderboard is a tool designed to compare and analyze the performance of text-to-video generation models. It provides a clear and organized way to display leaderboard tables, showcasing video scores and evaluation data. This tool is essential for researchers and developers to track progress, identify top-performing models, and make data-driven decisions.
• Score Display: Shows video scores in a structured leaderboard format.
• Model Comparison: Allows side-by-side comparison of different models.
• Real-Time Data Updates: Reflects the latest evaluation results.
• Interactive Tables: Enables sorting, filtering, and searching functionalities.
• Data Visualization: Includes charts to represent trends and performance metrics.
• Customization: Users can filter by specific criteria or metrics.
What is a "model" in the context of VideoScore Leaderboard?
A model refers to a specific text-to-video generation algorithm or system being evaluated.
Can I customize the leaderboard to show only specific models?
Yes, users can filter the leaderboard to display only the models they are interested in.
How are the video scores calculated?
Video scores are calculated using predefined evaluation metrics, which may vary depending on the dataset or use case.