Advancing the state of the art in computer vision with self-supervised Vision Transformers @AIatMeta
Advancing the state of the art in computer vision with self-supervised Vision Transformers  @AIatMeta
Uploaded April 2021 | Updated September 2026, 3 days ago
Working with @Inria researchers, we’ve developed DINO, a method to train Vision Transformers (ViT) with no supervision. This model can discover and segment objects in an image or video with no supervision. #computervision Get the code: ai.facebook.com/blog/dino-paws-computer-vision-with-self-supervised-transformers-and-10x-more-efficient-training
Advancing the state of the art in computer vision with self-supervised Vision TransformersHabitat 2.0: Training home assistants to rearrange their habitatYann LeCun on the future of deep learning hardwareFacebook AI Research | FreedomIs human led mathematics over? Panel with Joelle Pineau, Timothy Gowers & Yann LeCun | Meta AIReimagining Metas Infrastructure for the AI Age | AI at MetaIntroducing SAM 3D: a New Standard for 3D Object & Human Reconstruction from a Single ImageThe first AI model that translates 100 languages without relying on English dataHow does AI learn to finish your sentences? Learn about Smart ComposeIntroducing Meta Segment Anything Model 3 (SAM 3): Unified Detection, Segmentation & TrackingOrigin Stories | AI at MetaPowered by AI: Engineering new shopping experiences
AI at Meta |

Advancing the state of the art in computer vision with self-supervised Vision Transformers

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER