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Vitpose Base Coco Aic Mpii

Developed by usyd-community
ViTPose is a human pose estimation model based on Vision Transformer, achieving outstanding performance on benchmarks like MS COCO through simple architectural design.
Downloads 38
Release Time : 1/8/2025

Model Overview

ViTPose uses a standard Vision Transformer as the backbone network combined with a lightweight decoder for human pose estimation, supporting parameter scaling from 100 million to 1 billion.

Model Features

Simple Architecture
Uses only standard Vision Transformer structure without complex domain-specific design knowledge
Exceptional Scalability
Parameter scale can expand from 100 million to 1 billion, establishing new frontiers in performance-throughput
Flexible Training
Supports various attention types, input resolutions, pretraining, and fine-tuning strategies
Knowledge Transfer
Supports transferring knowledge from large models to small models via knowledge tokens

Model Capabilities

Human Pose Estimation
Multi-Person Keypoint Detection
Occlusion Scenario Analysis

Use Cases

Health & Fitness
Exercise Pose Analysis
Real-time monitoring of exercise movement standardization
Provides precise positional feedback for 17 keypoints
Smart Surveillance
Behavior Analysis
Abnormal behavior detection in public spaces
Maintains 80.9 AP accuracy even in occluded scenarios
Digital Entertainment
Motion Capture
Game character motion driving
Supports real-time multi-person pose estimation
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