VLMEvalKit Eval Results in video understanding benchmark
Track points in a video
Create a video by syncing spoken audio to an image
Remove/Change background of video.
Track objects in your video by marking points
Generates a sound effect that matches video shot
Generate realistic talking heads from image+audio
Create GIFs with FLUX, no GPU required
Generate animated characters from images
Audio Conditioned LipSync with Latent Diffusion Models
Generate responses to video or image inputs
Download YouTube videos or audio
Apply the motion of a video on a portrait
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.