DINOv3 is a series of general-purpose visual foundation models that can outperform specialized state-of-the-art techniques on a wide range of visual tasks without fine-tuning. This model can generate high-quality dense features and performs excellently in various visual tasks, significantly surpassing previous self-supervised and weakly-supervised foundation models.

Computer VisionTransformersEnglish

DINOv3 is a series of general visual foundation models developed by Meta AI. Without fine-tuning, it can outperform specialized state-of-the-art models in a wide range of visual tasks. This model uses self-supervised learning to generate high-quality dense features and performs excellently in various tasks such as image classification, segmentation, and depth estimation.

Computer VisionTransformersEnglish

DINOv3 is a series of general visual foundation models developed by Meta AI. It can outperform specialized advanced models in various visual tasks without fine-tuning. The model adopts the Vision Transformer architecture and is pre-trained on 1.689 billion web images. It can generate high-quality dense features and performs excellently in tasks such as image classification, segmentation, and retrieval.

Computer VisionTransformersEnglish

DINOv3 is a series of general-purpose visual foundation models that can outperform specialized state-of-the-art models on a wide range of visual tasks without fine-tuning. The model uses self-supervised learning to generate high-quality dense features and performs excellently in various visual tasks, significantly surpassing previous self-supervised and weakly supervised foundation models.

Computer VisionTransformersEnglish

DINOv3 is a series of general visual foundation models that can outperform specialized state-of-the-art techniques in a wide range of visual tasks without fine-tuning. The model generates high-quality dense features through self-supervised learning and performs excellently in various visual tasks, significantly surpassing previous self-supervised and weakly supervised foundation models.

Computer VisionTransformersEnglish

MOMENT is a series of general-purpose foundational models for time series analysis, supporting various tasks such as forecasting, classification, anomaly detection, etc., with out-of-the-box and fine-tuning capabilities.

Scientific ComputingTransformers

MOMENT is a series of foundation models for general time series analysis, supporting various time series tasks with out-of-the-box effectiveness and performance improvements through fine-tuning.

Scientific ComputingTransformers

MOMENT is a series of general-purpose time series analysis foundation models that support multiple time series analysis tasks, offering out-of-the-box effectiveness and performance enhancement through fine-tuning.

Scientific ComputingTransformers