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Top Foundation Vision Models
Foundation models are large models that you can use without prior training. You can use foundation models to auto-label data for use in training a smaller, real-time vision model.
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Foundation Vision
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LLMS with Vision Capabilities
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Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using
Roboflow Inference
.
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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
GroundingDINO
Grounding DINO is a zero-shot object detection model made by combining a Transformer-based DINO detector and grounded pre-training.
Object Detection
Deploy with Roboflow
YOLO-World
YOLO-World is a zero-shot object detection model.
Object Detection
Deploy with Roboflow
PaliGemma
PaliGemma is a vision language model (VLM) by Google that has multimodal capabilities.
Vision Language
Deploy with Roboflow
GPT-4o
GPT-4o is OpenAI’s third major iteration of GPT-4 expanding on the capabilities of GPT-4 with Vision
Vision Language
Deploy with Roboflow
OpenAI CLIP
CLIP (Contrastive Language-Image Pre-Training) is an impressive multimodal zero-shot image classifier that achieves impressive results in a wide range of domains with no fine-tuning. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.
Video Classification
Deploy with Roboflow
LLaVA-1.5
LLaVA is an open source multimodal language model that you can use for visual question answering and has limited support for object detection.
Object Detection
Deploy with Roboflow
SigLIP
SigLIP is an image embedding model defined in the "Sigmoid Loss for Language Image Pre-Training" paper.
Classification
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.
Classification
Deploy with Roboflow
4M
The 4M model is a versatile multimodal Transformer model developed by EPFL and Apple, capable of handling a handful of vision and language tasks.
Object Detection
Deploy with Roboflow
CoDet
CoDet is an open vocabulary zero-shot object detection model.
Object Detection
Deploy with Roboflow
Kosmos-2
Kosmos-2 is a multimodal language model capable of object detection and grounding text in images.
Object Detection
Deploy with Roboflow
OWLv2
OWLv2 is a transformer-based object detection model developed by Google Research. OWLv2 is the successor to OWL ViT.
Object Detection
Deploy with Roboflow
OWL ViT
OWL-ViT is a transformer-based object detection model developed by Google Research.
Object Detection
Deploy with Roboflow
GPT-4 with Vision
GPT-4 with Vision is a multimodal language model developed by OpenAI.
Object Detection
Deploy with Roboflow
MobileCLIP
MobileCLIP is an image embedding model developed by Apple and introduced in the "MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training" paper
Classification
Deploy with Roboflow
Anthropic Claude 3
Vision Language
Deploy with Roboflow
Google Gemini
Gemini is a family of Large Multimodal Models (LMMs) developed by Google Deepmind focused specifically on multimodality.
Vision Language
Deploy with Roboflow
PaliGemma-2
PaliGemma-2 is a multimodal model developed by Google.
Vision Language
Deploy with Roboflow
Visual Question Answering
Image Tagging
Image Similarity
Image Captioning
Zero-shot Detection
Real-Time Vision
Image Embedding
LLMS with Vision Capabilities
Multimodal Vision
Foundation Vision