OpenVision-ViT-Tiny-Patch16-160 Open-source Visual Encoder - Cost-effective with Support for Multimodal Learning

Openvision Vit Tiny Patch16 160

Developed by UCSC-VLAA

OpenVision is a fully open, cost-effective advanced visual encoder family focused on multimodal learning.

Downloads 30

Release Time : 5/6/2025

Model Overview

OpenVision is a visual encoder family for multimodal learning, designed to provide efficient and open visual feature extraction solutions.

Fully Open

The model is completely open, facilitating research and commercial applications.

Cost-effective

Maintains high performance while having low computational costs.

Multimodal Learning

Supports multimodal learning, capable of handling joint tasks involving vision and language.

Image Feature Extraction

Multimodal Learning

Computer Vision

Image Classification

Use OpenVision to extract image features for classification tasks.

Object Detection

Leverage OpenVision's feature extraction capabilities for object detection.

Multimodal Learning

Visual Question Answering

Combine text and image features for visual question answering tasks.

Image Captioning

Use OpenVision to extract image features for generating natural language descriptions.

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