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- Introduction:
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- Task:
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- SAM Testing:
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- Model Theory:
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- Model Code Overview:
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- Image Encoder Code:
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- Prompt Encoder Code:
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- Mask Decoder Code:
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- Data & Engine:
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- Zero-Shot Results:
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- Limitation:
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- Conclusion:
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive deep into Meta's groundbreaking Segment Anything Model (SAM) in this comprehensive technical video that demystifies the revolutionary approach to image segmentation. Learn how SAM achieves impressive zero-shot performance across various computer vision tasks through detailed explanations of its architecture, including the image encoder, prompt encoder, and mask decoder components. Follow along with code analysis and implementation details while exploring the model's theory, testing methodology, and practical applications. Examine the underlying data engine, evaluate zero-shot results, and understand key limitations of this foundational model. The presentation includes hands-on demonstrations using tools like TLDRAW for code analysis, making complex concepts accessible through clear visual explanations and real-world examples.

Segment Anything Model (SAM) - Deep Dive into Meta's Image Segmentation Foundation Model

Yacine Mahdid
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