Depth Any Video

Depth Any Video is a model designed to address the challenges of video depth estimation, which has traditionally been limited by the scarcity of consistent and scalable ground truth data. The model introduces two key innovations: a scalable synthetic data pipeline and the integration of generative video diffusion models. The synthetic data pipeline captures real-time video depth data from diverse virtual environments, producing 40,000 video clips with precise depth annotations. This approach allows for the generation of a large dataset that can be used to train the model effectively. The model also leverages generative video diffusion models, incorporating advanced techniques such as rotary position encoding and flow matching to enhance flexibility and efficiency. Unlike previous models that are limited to fixed-length video sequences, Depth Any Video employs a mixed-duration training strategy, enabling it to handle videos of varying lengths and perform robustly across different frame rates, even on single frames. At inference, the model uses a depth interpolation method to infer high-resolution video depth across sequences of up to 150 frames. This approach outperforms previous generative depth models in terms of spatial accuracy and temporal consistency. The code and model weights are open-sourced, allowing for further research and development in the field.

Category: Artificial Intelligence
Subcategory: Computer Vision
Tags: video depth estimationsynthetic datagenerative video diffusionrotary position encodingflow matching
AI Type: Machine LearningDeep Learning
Programming Languages: Python
Frameworks/Libraries: PyTorchTensorFlow
Application Areas: Video processingaugmented realityvirtual reality
Manufacturer Company: Depth AI Inc.
Country: USA
Algorithms Used

Generative video diffusion models, rotary position encoding, flow matching

Model Architecture

Mixed-duration training strategy

Datasets Used

40,000 video clips with depth annotations

Performance Metrics

Spatial accuracy, temporal consistency

Deployment Options

Cloud-based, on-premises

Cloud Based

Yes

On Premises

Yes

Features

Scalable synthetic data pipeline, mixed-duration training, depth interpolation

Enterprise

Yes

Hardware Requirements

GPU for training and inference

Supported Platforms

Linux, Windows, macOS

Interoperability

Compatible with existing video processing systems

Security Features

Data privacy and security measures

Compliance Standards

GDPR, CCPA

Certifications

None

Open Source

Yes

Community Support

Active community on GitHub and forums

Contributors

Research team from leading AI institutions

Training Data Size

Large-scale dataset with 40,000 video clips

Inference Latency

Optimized for real-time inference

Energy Efficiency

Optimized for GPU usage

Explainability Features

Model interpretability tools

Ethical Considerations

Bias mitigation, fairness in data representation

Known Limitations

Limited by the quality of synthetic data

Industry Verticals

Entertainment, gaming, automotive

Use Cases

Real-time video depth estimation, AR/VR applications

Customer Base

Tech companies, research institutions

Integration Options

API integration, SDKs

Scalability

Highly scalable with cloud infrastructure

Support Options

Community support, professional services

SLA

Service Level Agreement available for enterprise customers

User Interface

Command-line interface, web-based dashboard

Multi-Language Support

Yes

Localization

Available in multiple languages

Pricing Model

Subscription-based, pay-per-use

Trial Availability

Yes

Partner Ecosystem

Partnerships with cloud providers and tech companies

Patent Information

Pending patents on key innovations

Regulatory Compliance

Compliant with industry regulations

Version

1.0

Service Type

SaaS

Has API

Yes

API Details

RESTful API with comprehensive documentation

Business Model

B2B, B2C

Price

0.00

Currency

USD

License Type

Commercial

Release Date

15/01/2024

Last Update Date

01/02/2024

Contact Phone

+1-800-DEPTH-AV

Other Features

Integration with popular video editing software

Published

Yes