Belangrijkste concepten
MiniGPT4-Video, a multimodal large language model, effectively processes both visual and textual data in videos, enabling comprehensive understanding and outperforming existing state-of-the-art methods on various video benchmarks.
Samenvatting
The paper introduces MiniGPT4-Video, a multimodal large language model (LLM) designed for video understanding. The model is capable of processing both visual and textual data from videos, allowing it to comprehend the complexities of video content.
Key highlights:
- MiniGPT4-Video builds upon the success of MiniGPT-v2, which excelled in translating visual features into the LLM space for single images.
- The proposed model extends this capability to process a sequence of video frames, enabling it to understand the temporal dynamics of videos.
- MiniGPT4-Video incorporates textual conversations (subtitles) alongside visual content, allowing the model to effectively answer queries involving both visual and text components.
- The model outperforms existing state-of-the-art methods on various video benchmarks, including MSVD, MSRVTT, TGIF, and TVQA.
- The authors leverage a three-stage training pipeline, including large-scale image-text pair pretraining, large-scale video-text pair pretraining, and video question-answering instruction fine-tuning.
- The model's performance is evaluated using the Video-ChatGPT benchmark, open-ended questions, and multiple-choice questions, demonstrating its superior capabilities in video understanding.
Statistieken
"MiniGPT4-Video outperforms existing state-of-the-art methods by notable margins of 4.22%, 1.13%, 20.82%, and 13.1% on the MSVD, MSRVTT, TGIF, and TVQA benchmarks, respectively."
"The proposed model achieves state-of-the-art performance in all five dimensions (Information Correctness, Detailed Orientation, Contextual Understanding, Temporal Understanding, and Consistency) of the Video-ChatGPT benchmark when using subtitles as input."
Citaten
"MiniGPT4-Video offers a compelling solution for video question answering, effectively amalgamating visual and conversational comprehension within the video domain."
"By directly inputting both visual and textual tokens, MiniGPT4-Video empowers the Language Modeling Model (LLM) to grasp the intricate relationships between video frames, showcasing promising proficiency in understanding temporal dynamics within video content."