Macks is a visual AI platform for B2B product brands like lighting and furniture, aiming to cut content creation costs via automated workflows. Integrating the DINO-X API into our segmentation pipeline has significantly improved user experience, making workflows more intuitive and interactive.

We make product visualization software for interior design/ furniture users, using DINO-X for object detection.I have tested many models for this use case and have settled on the DINO-X models because they offer unparalleled recall, precision, and robustness under poor lighting conditions.

DINO-X is what you need! It delivers unparalleled performance and versatility by achieving exceptional accuracy on rare and long-tailed objects. This capability is critical for enabling the transition of foundation models from research to practical applications, providing robust support for downstream tasks.

Visual grounding is a core component of our GUI agent projects, requiring an object detection model to identify interactive elements. We found that Grounding DINO 1.6 performed exceptionally well on this task, even outperforming some models specifically designed for it. Very cool!

Muda is built on personalization to ensure every outfit recommendation feels tailored to each individual’s body and style. Dino-X makes accurate clothing detection and segmentation possible which is needed for the virtual try on model.

Our product creates practical AI textile image generation for designers, using DINO-X to extract objects from images. These are matched in a database for pseudo-RAG, then fed to a fine-tuned model for accurate designs—DINO-X bridges AI visuals and real textile use.

I am building a pipeline that uses Grounding DINO to create an AI assistant that can see anything and do anything. I really love grounding dino and happy to build something amazing with it.

DINO-X is a great model. Without it, I have to do a lot more with less competetive models and couldn't achieve such a remarkable result.