D

Dpt Swinv2 Base 384

Developed by Intel
The DPT (Dense Prediction Transformer) model is trained on 1.4 million images for monocular depth estimation. This model uses Swinv2 as the backbone network and is suitable for high-precision depth prediction tasks.
Downloads 182
Release Time : 12/10/2023

Model Overview

The DPT model is a vision transformer-based dense prediction model specifically designed for monocular depth estimation tasks. This version employs Swinv2 as the backbone network, capable of predicting depth information from a single image.

Model Features

High-precision depth estimation
Trained on 1.4 million images, capable of predicting accurate depth information from a single image
Swinv2 backbone network
Utilizes the advanced Swinv2 transformer architecture as the backbone network, featuring powerful feature extraction capabilities
Zero-shot prediction
Capable of depth estimation without fine-tuning for specific scenes

Model Capabilities

Monocular depth estimation
Image depth prediction
3D scene understanding

Use Cases

Computer vision
3D scene reconstruction
Reconstruct 3D scenes from a single image
Generate precise depth maps
Augmented reality
Provide scene depth information for AR applications
Enable more realistic virtual object placement
Robotic vision
Autonomous navigation
Provide environmental depth perception for robots
Assist in path planning and obstacle avoidance
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