ShareGPT4Video

Preview：

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Introduce：

The ShareGPT4Video series is designed to facilitate video understanding for large video-language models (LVLMs) and video generation for text-to-video models (T2VMs) through intensive and precise captioning. The series includes: 1) ShareGPT4Video, 40K GPT4V annotated intensive video captioning, developed through carefully designed data filtering and annotation strategies. 2) ShareCaptioner-Video, an efficient and powerful arbitrary video captioning model, by its annotated 4.8M high quality aesthetic video. 3) ShareGPT4Video-8B, a simple but superior LVLM that achieves optimal performance in three advanced video benchmarks.

Stakeholders:
The ShareGPT4Video series is suitable for researchers and developers who need to do video content analysis and generation, especially those professionals who focus on video understanding and text-to-video conversion technologies. It provides powerful support for automatic annotation of video content, video summary generation and video generation tasks.
Usage Scenario Examples:

Video content analysis and captioning generation of shorelines and historic buildings on the Amalfi Coast using the ShareGPT4Video model.
Use ShareCalitioner-Video to generate descriptive captions for an abstract art video to enhance the artistic expression of the video.
Through the ShareGPT4Video-8B model, we can realize the in-depth understanding of a video of fireworks display and generate related descriptions.

The features of the tool:

ShareGPT4Video, a 40K high quality video covering a wide range of categories, with captions containing a wealth of world knowledge, object properties, camera movements and detailed and accurate time descriptions of events.
ShareCalitioner-Video, which efficiently generates high-quality captions for any video, has proven its effectiveness in 10-second text-to-video generation tasks.
ShareGPT4Video-8B, a new LVLM, validated its effectiveness on several current LVLM architectures and demonstrated its superior performance.
A differentiated video captioning strategy is designed, which is stable, scalable and efficient, and can be used to generate video captioning with arbitrary resolution, aspect ratio and length.
The ShareGPT4Video dataset contains a large number of high-quality video-subtitle pairs covering diverse content, including wildlife, cooking, sports, landscapes and more.
ShareCalitioner-Video is a 4-in-1 superior video captioning model with quick captioning, sliding captioning, clip summary and prompt heavy captioning capabilities.

Steps for Use:

Visit ShareGPT4Video’s official website for models and datasets.
Choose the right model for your needs, such as ShareGPT4Video or ShareCalitioner-Video.
Download and install the necessary software environments and dependency libraries.
Load the model and prepare video data.
Run the model to process the video, such as captioning generation or content analysis.
View the generated captions or analysis results and develop further applications as needed.

Tool’s Tabs: Video understanding, text to video