DINOv3 is Meta AI Research's reference PyTorch implementation and model collection for a family of self-supervised vision foundation models. It provides high-resolution dense patch features, multiple pretrained backbones (ViT and ConvNeXt variants), pretrained heads for classification/detection/segmentation/depth, and integration examples for PyTorch Hub and Hugging Face. The repo contains training and evaluation scripts, notebooks, and instructions to obtain model weights.
Isaac Lab is an open-source, GPU-accelerated robotics learning framework built on NVIDIA Isaac Sim. It provides high-fidelity physics and sensor simulation, ready-to-train environments and robot models, and integrations for reinforcement and imitation learning workflows to accelerate sim-to-real research and large-scale robot training.
DINOv3 is a reference implementation and model release from Meta AI Research (FAIR) for a family of self-supervised vision foundation models producing high-quality dense patch-level features. The project focuses on versatile vision backbones (ViT and ConvNeXt variants) pretrained on large datasets and adapted to a variety of downstream tasks without or with minimal fine-tuning.
