openvision-vit-base-patch8-384 Open-source Visual Encoder - An Efficient Solution for Multimodal Learning

Openvision Vit Base Patch8 384

Developed by UCSC-VLAA

OpenVision is a fully open-source and cost-effective family of advanced visual encoders, specifically designed for multimodal learning.

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Release Time : 5/6/2025

Model Overview

OpenVision offers a series of visual encoders aimed at supporting multimodal learning tasks, featuring efficiency and open-source accessibility.

Fully open-source

Model code and weights are fully open-source, facilitating research and commercial use.

Cost-effective

Designed with computational efficiency in mind, suitable for resource-constrained environments.

Multimodal support

Specifically designed for multimodal learning tasks, supporting the integration of vision with other modalities.

Image feature extraction

Multimodal learning

Computer vision

Image understanding

Extract image features for subsequent tasks such as classification and detection.

Multimodal applications

Vision-language models

Combine visual and linguistic information for tasks like image caption generation.

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