VLMEvalKit Eval Results in video understanding benchmark
Generate animated videos from configuration files
Leaderboard and arena of Video Generation models
Audio-based Lip Sync for Talking Head Video Editing
Easily remove your videos background!
Generate Talking avatars from Text-to-Speech
Generate music videos from text descriptions
Generate animated videos from text prompts
Creator Friendly Text-to-Video
Generate videos from text or images
Create an animated video from audio and a reference image
Browse robotic datasets visually
Generate and apply matching music background to video shot
The Open VLM Video Leaderboard is a tool designed to evaluate and compare video models based on the Video Understanding Benchmark. It provides a comprehensive platform to assess and rank video models, offering insights into their performance across various video understanding tasks. This leaderboard is part of the VLMEvalKit, a framework used for evaluating video model performance.
• Real-Time Tracking: Stay updated with the latest video model performances and rankings. • Interactive Visualizations: Explore model comparisons and benchmark results through intuitive graphs and charts. • Filtering Options: Narrow down results based on specific metrics or tasks to focus on relevant data. • Benchmarking: Compare video models against standard benchmarks and other models. • Download Results: Export performance data for offline analysis and further research.
What is the purpose of the Open VLM Video Leaderboard?
The Open VLM Video Leaderboard is designed to provide a centralized platform for evaluating and comparing video models based on video understanding tasks. It helps researchers and developers identify top-performing models and track improvements over time.
Can I submit my own video model for evaluation?
Yes, the Open VLM Video Leaderboard allows submissions of video models for evaluation. Please refer to the official documentation for submission guidelines and requirements.
How often is the leaderboard updated?
The leaderboard is updated regularly to include new models and re-evaluate existing ones. Updates are typically announced on the official platform or through associated communication channels.