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Table Of Contents
- Introduction
- SAM 2 : Real Time Object Segmentation Model By Meta
- Meta Segment Anything Model 2 design
- What’s New In SAM 2?
- SAM 2 Web Based Preview
- Try Demo Of SAM 2 Object Segmentation Model
- Download The Dataset Of SAM 2
- Summary
- References
Introduction
In this post we discuss about, meta ai’s segment anything model 2 which is just released by meta. and you are looking, SAM 2 : Real Time Object Segmentation Model By Meta.
SAM 2 : Real Time Object Segmentation Model By Meta
Meta Segment Anything Model 2 design
- The SAM 2 model extends the promptable capability of SAM to the video domain by adding a per session memory module that captures information about the target object in the video.
- This allows SAM 2 to track the selected object throughout all video frames, even if the object temporarily disappears from view, as the model has context of the object from previous frames.
- SAM 2 also supports the ability to make corrections in the mask prediction based on additional prompts on any frame.
- SAM 2’s streaming architecture – which processes video frames one at a time – is also a natural generalization of SAM to the video domain.
- When SAM 2 is applied to images, the memory module is empty and the model behaves like SAM.
What’s New In SAM 2?
- SAM 2 works with video where the original SAM only worked with still images
- It outperforms SAM on its 23 dataset zero-shot benchmark suite, while outperforms other approaches across 17 zero-shot video datasets
- The new SA-V dataset is a game-changer, 4.5 times larger than previous datasets with 53 times more annotations. (51,000 videos and over 600,000 spatio-temporal masks)
- Released under the Apache 2.0 license, meaning anyone can use it to create innovative applications.
Meta said the AI model can help ease the process of video editing or AI-based video generation, as well as to power new experiences in the company’s mixed-reality ecosystem.
SAM 2 Web Based Preview
Try Demo Of SAM 2 Object Segmentation Model
Download The Dataset Of SAM 2
- SAM 2 significantly outperforms previous approaches on interactive video segmentation across 17 zero-shot video datasets and requires approximately three times fewer human-in-the-loop interactions.
- SAM 2 outperforms SAM on its 23 dataset zero-shot benchmark suite, while being six times faster.
- SAM 2 excels at existing video object segmentation benchmarks (DAVIS, MOSE, LVOS, YouTube-VOS) compared to prior state-of-the-art models.
- Inference with SAM 2 feels real-time at approximately 44 frames per second.
- SAM 2 in the loop for video segmentation annotation is 8.4 times faster than manual per-frame annotation with SAM.