Vision Models by Meta

Explore computer vision and multimodal models developed by Meta.

Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using Roboflow Inference.

Showing

of

models.

Segment Anything Model (SAM)

Segment Anything (SAM) is an image segmentation model developed by Meta Research, capable of doing zero-shot segmentation.

Instance Segmentation

Deploy with Roboflow

Segment Anything 2

Segment Anything 2 (SAM 2) is a real-time image and video segmentation model.

Instance Segmentation

Deploy with Roboflow

Detectron2

Detectron2 is model zoo of it's own for computer vision models written in PyTorch.

Object Detection

Deploy with Roboflow

DETR

Detection Transformer (DETR) is an end-to-end object detection model implemented using the Transformer architecture.

Object Detection

Deploy with Roboflow

FastSAM

FastSAM is an image segmentation model trained using 2% of the data in the Segment Anything Model SA-1B dataset.

Instance Segmentation

Deploy with Roboflow

DETIC

Detic is an open source segmentation model developed by Meta Research and released in 2022.

Instance Segmentation

Deploy with Roboflow

MetaCLIP

MetaCLIP is a zero-shot classification and embedding model developed by Meta AI.

Deploy with Roboflow

CoDet

CoDet is an open vocabulary zero-shot object detection model.

Object Detection

Deploy with Roboflow

VLPart

VLPart, developed by Meta Research, is an object detection and segmentation model that works with an open vocabulary

Object Detection

Deploy with Roboflow

Visual Question Answering

Image Similarity

Image Captioning

Zero-shot Detection

Real-Time Vision

Image Embedding

LLMS with Vision Capabilities

Multimodal Vision

Foundation Vision