Inside DINOv2: Meta AI’s New Self-Supervised Learning Model for Computer Vision

Author(s): Jesus Rodriguez

Originally published on Towards AI.

The model uses a novel architecture to remove the dependencies on text fine tuning and exhibits interesting emerging properties.

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Natural Language Processing has adopted learning task-agnostic pretrained representations as a standard. The use of these features without fine-tuning can achieve better performance on downstream tasks than task-specific models…. Read the full blog for free on Medium.

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Published via Towards AI