Task
Zero Shot Object Detection
O
google/owlvit-base-patch32
Zero Shot Object Detection·google· 219.9K· 149
transformers
apache-2.0
Zero Shot Object Detection
153.2M params
arxiv:2205.06230license:apache-2.0region:us
The OWL-ViT (short for Vision Transformer for Open-World Localization) was proposed in Simple Open-Vocabulary Object Detection with Vision Transformers by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby. OWL-ViT is a zero-s
# pull & run locally
pip install mlforge-sdk && mlforge pull google/owlvit-base-patch32
pip install mlforge-sdk && mlforge pull google/owlvit-base-patch32
Model details
Provider
google
Framework
transformers
Parameters
153.2M
Size
4.6 GB
License
apache-2.0
Downloads
219.9K
Likes
149
Paper
arXiv:2205.06230
Updated
2023-12-12
About google/owlvit-base-patch32
The OWL-ViT (short for Vision Transformer for Open-World Localization) was proposed in Simple Open-Vocabulary Object Detection with Vision Transformers by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby. OWL-ViT is a zero-shot text-conditioned object detection model that can be used to query an image with one or multiple text queries.