OpenGVLab/InternVideo

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2368 stars · 159 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

InternVideo is a series of open-source video foundation models for multimodal video understanding, spanning generative and discriminative learning, long-context video MLLMs, and video agents. It also releases InternVid, a large-scale video-text dataset with hundreds of millions of pairs for training and evaluation.

Use cases

• understand and answer questions about videos with a multimodal LLM
• retrieve videos using text queries
• classify human actions in video clips
• localize actions temporally in long videos
• train a video-text model on a large video dataset
• run zero-shot video classification benchmarks
• build an agent that reasons over long video content

When to choose

• you need state-of-the-art pretrained video understanding models with released checkpoints
• you want a large-scale video-text dataset for pretraining or fine-tuning
• you need video retrieval, QA, or action recognition in one model family
• you are researching multimodal video-language models

When to avoid

• you only need lightweight real-time video processing without deep models
• you lack GPU resources, as the flagship models are 1B-8B parameters
• you need production video streaming or transcoding rather than understanding
• you need a plug-and-play app rather than research code

Facets

library · maturity active

machine-learning deep-learning video-processing nlp rag agent-framework artificial-intelligence deep-learning computer-vision large-language-models python cross-platform video-foundation-models multimodal video-text-dataset video-retrieval video-question-answering action-recognition zero-shot-classification contrastive-learning self-supervised-learning instruction-tuning vision-transformer eccv2024 video ai-agents gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="OpenGVLab/InternVideo")