VLMEvalKit Eval Results in video understanding benchmark
Generate lip-synced video from video/image and audio
Generate subtitled videos from YouTube links
Create videos with FFMPEG + Qwen2.5-Coder
input text, extracting key themes, emotions, entities,
Dense Grounded Understanding of Images and Videos
Generate animated characters from images
Video Super-Resolution with Text-to-Video Model
text-to-video
Create video ads from product names
Leaderboard and arena of Video Generation models
Generate a video from text with voice narration
Open VLM Video Leaderboard is a comprehensive platform designed for evaluating and comparing video understanding models. It serves as a central hub for users to browse and analyze the performance of various video models based on standardized benchmarks. Developed as part of the VLM Eval Kit, this leaderboard provides a transparent and accessible way to track advancements in video understanding technologies.
• Comprehensive Model Tracking:.Monitors performance of leading video models across multiple benchmark datasets.
• Real-Time Updates: Offers the latest evaluation results, ensuring users stay informed about the newest developments.
• Customizable Comparison: Enables users to filter and compare models based on specific criteria such as dataset, task, or performance metrics.
• Transparency: Provides detailed information about model architectures, training procedures, and evaluation metrics for full accountability.
• Support for Diverse Tasks: Covers a wide range of video-related tasks, including video captioning, question answering, and action recognition.
• User-Friendly Interface: Designed with an intuitive layout to make it easy for researchers and developers to navigate and analyze data.
• Regular Updates: Continuously expanded with new models, datasets, and features to reflect the evolving landscape of video understanding.
What types of models are included in the Open VLM Video Leaderboard?
The leaderboard includes a wide range of video models, from state-of-the-art research models to open-source implementations, focusing on tasks like video captioning, question answering, and action recognition.
How often is the leaderboard updated?
The leaderboard is updated regularly to reflect new model submissions, updates to existing models, and the addition of new benchmark datasets.
Can I submit my own model for evaluation?
Yes, the platform allows researchers and developers to submit their models for evaluation. Visit the submission guidelines section for detailed instructions on how to participate.