Videomae Base Finetuned Ucf101 Subset
A video classification model fine-tuned on a subset of UCF101 based on the VideoMAE base model, achieving 95.22% accuracy
Downloads 17
Release Time : 1/15/2023
Model Overview
This model is a video understanding model based on the VideoMAE architecture, specifically fine-tuned for a subset of the UCF101 dataset, suitable for video action recognition tasks
Model Features
High Accuracy
Achieves 95.22% classification accuracy on the UCF101 subset
Self-supervised Pre-training
Utilizes the VideoMAE architecture with masked autoencoder for pre-training
Efficient Fine-tuning
Performs few-shot fine-tuning on the base model for rapid adaptation to specific tasks
Model Capabilities
Video Action Recognition
Video Content Classification
Spatio-temporal Feature Extraction
Use Cases
Video Analysis
Action Recognition System
Identifies human actions and behaviors in videos
Achieves 95.22% accuracy on the UCF101 subset
Video Content Classification
Automatically classifies and labels video content
Featured Recommended AI Models
Š 2025AIbase