White Paper

Unlocking visual insights with Vision Transformers

We’ve explored the advantages, applications, and economic benefits of Vision Transformers in computer vision tasks, redefining image analysis for improved performance and efficiency.

Vision Transformers

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#Computer Vision
#Deep Learning
#Self Attention

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What are Vision Transformers?

Vision Transformers (ViTs) are advanced deep learning architectures that are transforming computer vision tasks by delivering impressive performance, capturing global information effectively, and efficiently handling long-term dependencies, driving significant advancements in the field of image analysis.

The main technologies behind ViTs

The key idea behind Vision Transformers is to treat image data as a sequence of patches, or regions, and use attention mechanisms to capture the relationships between regions to make a prediction. Let’s focus on the two main technologies behind ViTs.

Core areas of application

ViTs in action: Reply’s testing

With the aim to validate Vision Transformers in real-world applications, we turned our attention to the DINO model. DINO, which stands for "self-distillation with NO label," is an advanced AI model for computer vision tasks introduced by Meta Al in 2021.

Through intensive development efforts, we successfully applied the DINO pre-trained ViT to automate tasks in various use cases. Specifically, we leveraged DINO to extract meaningful features and detect objects without being specifically trained for them. All the use cases encompassed integrating DINO into Spot, Boston Dynamics' most friendly and agile autonomous robot, to safely perform monitoring and inspection of industrial sites. As an example, after the integration, Spot could automatically read measurements from industrial processes and take data-driven actions accordingly, while being extremely data efficient. Reply has also evaluated VC-1, CLIP, SAM and Grounding DINO, all of which are driving breakthrough innovation in Computer Vision.

embark on a transformative journey in computer vision

Are you ready to unlock the potential of Vision Transformers? Connect with us to explore the latest applications and use cases.

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PRIVACY

I declare that I have read and fully understood the Privacy Notice and I hereby express my consent to the processing of my personal data by Reply SpA for marketing purposes, in particular to receive promotional and commercial communications or information regarding company events or webinars, using automated contact means (e.g. SMS, MMS, fax, email and web applications) or traditional methods (e.g. phone calls and paper mail).

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