

Sharegpt4video
Overview :
The ShareGPT4Video series aims to promote video understanding in large video-language models (LVLMs) and video generation in text-to-video models (T2VMs) through dense and precise captions. The series includes:
1) ShareGPT4Video, a dense video caption dataset of 40K GPT4V annotations, developed through carefully designed data filtering and annotation strategies.
2) ShareCaptioner-Video, an efficient and powerful video captioning model for any video, trained on its 4.8M high-quality aesthetic video dataset.
3) ShareGPT4Video-8B, a simple yet excellent LVLM that achieved top performance on three advanced video benchmark tests.
Target Users :
The ShareGPT4Video series is suitable for researchers and developers who need to analyze and generate video content, especially professionals focused on video understanding and text-to-video conversion technologies. It provides strong support for tasks such as automatic video annotation, video summarization generation, and video generation.
Use Cases
Use the ShareGPT4Video model to analyze video content and generate captions for the Amalfi Coast's coastline and historical architecture.
Utilize ShareCaptioner-Video to generate descriptive captions for an abstract art video, enhancing its artistic expression.
Leverage the ShareGPT4Video-8B model to deeply understand and generate descriptions for a fireworks display video.
Features
ShareGPT4Video contains 40K high-quality videos covering a wide range of categories. The captions include rich world knowledge, object attributes, detailed and precise temporal descriptions of camera movements, and events.
ShareCaptioner-Video efficiently generates high-quality captions for any video and has been validated for its effectiveness in 10-second text-to-video generation tasks.
ShareGPT4Video-8B, a new LVLM, validates its effectiveness on multiple current LVLM architectures and demonstrates its superior performance.
A differentiated video captioning strategy is designed, which is stable, scalable, and efficient for video captioning generation of any resolution, aspect ratio, and length.
The ShareGPT4Video dataset contains a large number of high-quality video-caption pairs covering diverse content, including wildlife, cooking, sports, and landscapes.
ShareCaptioner-Video is an exceptional four-in-one video captioning model with capabilities for fast captioning, sliding captioning, clip summarization, and prompt-based re-captioning.
How to Use
Visit the official ShareGPT4Video website to access the models and datasets.
Select the appropriate model based on your needs, such as ShareGPT4Video or ShareCaptioner-Video.
Download and install the necessary software environment and dependency libraries.
Load the model and prepare the video data.
Run the model to process the video, such as caption generation or content analysis.
View the generated captions or analysis results and proceed with further application development as needed.
Featured AI Tools

Sora
AI video generation
17.0M

Animate Anyone
Animate Anyone aims to generate character videos from static images driven by signals. Leveraging the power of diffusion models, we propose a novel framework tailored for character animation. To maintain consistency of complex appearance features present in the reference image, we design ReferenceNet to merge detailed features via spatial attention. To ensure controllability and continuity, we introduce an efficient pose guidance module to direct character movements and adopt an effective temporal modeling approach to ensure smooth cross-frame transitions between video frames. By extending the training data, our method can animate any character, achieving superior results in character animation compared to other image-to-video approaches. Moreover, we evaluate our method on benchmarks for fashion video and human dance synthesis, achieving state-of-the-art results.
AI video generation
11.4M