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Videomaev2 Large

Developed by OpenGVLab
VideoMAEv2-Large is a large-scale video feature extraction model pre-trained with self-supervision on the UnlabeldHybrid-1M dataset
Downloads 5,581
Release Time : 1/14/2025

Model Overview

This model employs a dual-mask strategy for video self-supervised learning, primarily designed for video feature extraction tasks

Model Features

Dual-mask Strategy
Utilizes an innovative dual-mask strategy for video self-supervised learning
Large-scale Pre-training
Pre-trained for 800 epochs on the UnlabeldHybrid-1M dataset
Video Feature Extraction
Feature extraction capabilities optimized for video content analysis

Model Capabilities

Video Feature Extraction
Video Content Analysis
Self-supervised Learning

Use Cases

Video Understanding
Video Classification
Extract video features for classification tasks
Video Content Analysis
Analyze video content features
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