MM-VID: Advancing Video Understanding with GPT-4V(ision)
We present MM-VID, an integrated system that harnesses the capabilities of
GPT-4V, combined with specialized tools in vision, audio, and speech, to
facilitate advanced video understanding. MM-VID is designed to address the
challenges posed by long-form videos and intricate tasks such as reasoning
within hour-long content and grasping storylines spanning multiple episodes.
MM-VID uses a video-to-script generation with GPT-4V to transcribe multimodal
elements into a long textual script. The generated script details character
movements, actions, expressions, and dialogues, paving the way for large
language models (LLMs) to achieve video understanding. This enables advanced
capabilities, including audio description, character identification, and
multimodal high-level comprehension. Experimental results demonstrate the
effectiveness of MM-VID in handling distinct video genres with various video
lengths. Additionally, we showcase its potential when applied to interactive
environments, such as video games and graphic user interfaces.
654088b86e8724317845f3dc
Kevin Lin
claimed_verified
2023-10-31T08:23:44.177Z
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Kevin Lin
user
kevinlin311tw
654088b86e8724317845f3dd
Faisal Ahmed
654088b86e8724317845f3de
Linjie Li
admin_assigned
2023-10-31T08:31:59.807Z
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Linjie Li
user
linjieli222
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Chung-Ching Lin
claimed_verified
2024-06-13T09:33:14.847Z
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CC Lin
user
cclin10
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Ehsan Azarnasab
admin_assigned
2023-10-31T08:29:43.166Z
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Ehsan Azarnasab
user
dashesy
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Zhengyuan Yang
admin_assigned
2023-10-31T08:29:53.627Z
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Zhengyuan Yang
user
zyang39
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Jianfeng Wang
admin_assigned
2023-10-31T08:30:31.121Z
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/avatars/0dbe862cde7e4bef25bedf860584d8c1.svg
Jianfeng Wang
user
amsword8
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Lin Liang
654088b86e8724317845f3e4
Zicheng Liu
654088b86e8724317845f3e5
Yumao Lu
654088b86e8724317845f3e6
Ce Liu
654088b86e8724317845f3e7
Lijuan Wang
admin_assigned
2023-10-31T08:31:40.453Z
6413521d4e5305c14f22e110
/avatars/a6f8d0573e678f79bc3c0b7897b818ce.svg
Lijuan Wang
user
Lijuan
MM-VID: Advancing Video Understanding with GPT-4V(ision)
We present MM-VID, an integrated system that harnesses the capabilities of
GPT-4V, combined with specialized tools in vision, audio, and speech, to
facilitate advanced video understanding. MM-VID is designed to address the
challenges posed by long-form videos and intricate tasks such as reasoning
within hour-long content and grasping storylines spanning multiple episodes.
MM-VID uses a video-to-script generation with GPT-4V to transcribe multimodal
elements into a long textual script. The generated script details character
movements, actions, expressions, and dialogues, paving the way for large
language models (LLMs) to achieve video understanding. This enables advanced
capabilities, including audio description, character identification, and
multimodal high-level comprehension. Experimental results demonstrate the
effectiveness of MM-VID in handling distinct video genres with various video
lengths. Additionally, we showcase its potential when applied to interactive
environments, such as video games and graphic user interfaces.
MM-VID integrates GPT-4V with specialized tools to transcribe and understand long-form, multimodal videos, supporting advanced tasks like audio description and character identification.
GPT-4V video-to-script generation large language models multimodal high-level comprehension