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Openvision Vit Large Patch14 336
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Openvision Vit Large Patch14 336

Developed by UCSC-VLAA
OpenVision is a fully open, cost-effective family of advanced visual encoders, specifically designed for multimodal learning.
Image Enhancement
Transformers
Open Source License:Apache-2.0#Multimodal Visual Encoding#Efficient Visual Feature Extraction#Open Pretrained Models
Downloads 34
Release Time : 5/6/2025

Model Overview

OpenVision offers a series of efficient visual encoders suitable for multimodal learning tasks, aiming to reduce computational costs while maintaining high performance.

Model Features

Open Source
Fully open model architecture and code, facilitating research and commercial applications.
Cost-Effective
Designed with computational efficiency in mind, reducing deployment and operational costs.
Multimodal Support
Optimized for multimodal learning tasks, suitable for combining visual and other modalities of data.

Model Capabilities

Image Feature Extraction
Multimodal Learning

Use Cases

Computer Vision
Image Classification
Use extracted image features for classification tasks.
Object Detection
Combine with other modules to achieve efficient object detection.
Multimodal Applications
Visual Question Answering
Combine text and visual information for question-answering tasks.
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