LLaVA and Video-LLaMA
These are complements: LLaVA provides the foundational vision-language instruction-tuning methodology for static images, which Video-LLaMA extends to the temporal and audio-visual domain for video understanding.
About LLaVA
haotian-liu/LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
LLaVA helps you understand and interact with images using natural language. You provide an image and ask questions or give instructions about its content, and it generates descriptive text, answers, or performs tasks like segmentation. This is ideal for anyone needing to extract insights from visuals, such as researchers analyzing images, content creators generating descriptions, or operations teams monitoring visual data.
About Video-LLaMA
DAMO-NLP-SG/Video-LLaMA
[EMNLP 2023 Demo] Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding
Video-LLaMA helps you understand the content of videos and images by answering your questions about them. You input a video or an image, and the model provides detailed text descriptions or answers based on both the visual and auditory information present. This is ideal for content analysts, researchers, or anyone needing to quickly extract insights from multimedia.
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