Meta's SAM 3.1 Video Model Tracks 16 Objects at Once
Meta has released SAM 3.1, an update to its video analysis model. The key change is multiplexing, which lets the model track up to 16 objects in a single computational pass instead of processing each one separately. Speed doubled to 32 fps on an H100, and the model needs less GPU memory. *Meta has been designated an extremist organization and is banned in Russia.
AI-processed from Meta AI Blog; edited by Hamidun News
Meta has unveiled SAM 3.1, a video neural network that tracks up to 16 objects in a single pass and runs twice as fast, reaching 32 frames per second on an H100 GPU.
What is a video neural network, and what is it for?
It is an AI model for analyzing video. For example, Meta's SAM 3.1 tracks up to 16 objects in a video simultaneously in real time, reaching 32 frames per second on an H100 GPU.
How is SAM 3.1 better than the previous video version?
The new architecture tracks up to 16 objects at once in a single computational pass, instead of the 16 separate passes needed before. This sped up processing by 2x and lowered GPU video memory requirements.
What is SAM 3.1's video processing speed?
32 frames per second on an H100 GPU, which is enough for real-time work.
*Meta has been designated an extremist organization and is banned in Russia.
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Key Questions Answered
What is a video neural network, and what is it for?
It is an AI model for analyzing video. For example, Meta's SAM 3.1 tracks up to 16 objects in a video simultaneously in real time, reaching 32 frames per second on an H100 GPU.
How is SAM 3.1 better than the previous video version?
The new architecture tracks up to 16 objects at once in a single computational pass, instead of the 16 separate passes needed before. This sped up processing by 2x and lowered GPU video memory requirements.
What is SAM 3.1's video processing speed?
32 frames per second on an H100 GPU, which is enough for real-time work. Meta has been designated an extremist organization and is banned in Russia.
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