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What is Ferret?

A sophisticated End-to-End MLLM has been developed to accommodate various types of references and effectively ground its responses. The Ferret Model employs a unique combination of Hybrid Region Representation and a Spatial-aware Visual Sampler, which facilitates detailed and adaptable referring and grounding functions within the MLLM framework. Serving as a foundational element, the GRIT Dataset consists of about 1.1 million entries, specifically designed as a large-scale and hierarchical dataset aimed at enhancing instruction tuning in the ground-and-refer domain. Moreover, the Ferret-Bench acts as a thorough multimodal evaluation benchmark that concurrently measures referring, grounding, semantics, knowledge, and reasoning, thus providing a comprehensive assessment of the model's performance. This elaborate configuration is intended to improve the synergy between language and visual information, which could lead to more intuitive AI systems that better understand and interact with users. Ultimately, advancements in these models may significantly transform how we engage with technology in our daily lives.

What is DreamActor-M1?

DreamActor-M1 is an advanced diffusion transformer system designed to create realistic human animations from a single image input. This groundbreaking framework facilitates detailed adjustments in both facial and body movements, showcasing its adaptability for a range of animation styles from intimate close-ups to detailed full-body sequences. It stands out for its ability to maintain temporal consistency across longer video clips, ensuring smooth transitions even in sections that aren't visible in the original images. By utilizing a hybrid motion guidance approach that combines implicit facial models, 3D head spheres, and skeletal frameworks, it provides users with sophisticated control over the nuances of animation. Furthermore, it incorporates complementary appearance guidance, leveraging multi-frame references to guarantee consistency in parts that are not directly observable. The training process is organized into three progressive stages, starting with a focus on body skeletons and head spheres, followed by the integration of facial models, and culminating in the optimization of all components for superior output. This careful and thorough training methodology significantly enhances the visual fidelity and realism of the animations produced. Ultimately, DreamActor-M1 represents a monumental leap forward in animation technology.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Apple

Date Founded

1976

Company Location

United States

Company Website

github.com/apple/ml-ferret

Company Facts

Organization Name

ByteDance

Date Founded

2012

Company Location

China

Company Website

dreamactor.org

Categories and Features

Categories and Features

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