Korewa AI is a revolutionary chat platform that utilizes artificial intelligence to bring anime characters to life, allowing users to create, publish, and interact with scarily realistic personalities, complete with memories and emotions, for a truly immersive experience.

This is Korewa.ai: AI-Powered Conversational Design Platform for Businesses

介绍

What is Korewa.AI?

Korewa.AI is a chat platform for anime fans, where users can interact with scarily realistic anime characters utilizing AI text models fine-tuned specifically for anime characters.

How does Korewa.AI work?

Korewa.AI allows users to create their own anime characters with advanced customization options, including personality, memory, and emotions. Users can upload images of their favorite characters, write up their memories, personality traits, and expressions. Once created, users can speak to their characters and watch as they come to life with advanced AI models.

Features of Korewa.AI

Advanced AI Character Customization

  • Give characters personality, memory, and emotions
  • Upload images of favorite characters
  • Write up memories, personality traits, and expressions

Visual-Novel-Style Character Animations

  • Characters can display emotions visually through images for various expressions

Publish Characters

  • Users can publicly publish characters they've created, allowing anyone to speak to them

Pricing

Demo ($0/mo)

  • Access to less-powerful demo AI model
  • Access to user-generated characters
  • Limited amount of messages/month
  • Draft editor for testing characters
  • Access to character creation
  • Ability to publish characters

Premium ($10/mo)

  • Access to premium AI model
  • Access to user-generated characters
  • Unlimited messages
  • Draft editor for testing characters
  • Access to character creation
  • Ability to publish characters

This - 替代

Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existing approaches gain controllability of generative adversarial networks (GANs) via manually annotated training data or a prior 3D model, which often lack flexibility, precision, and generality. In this work, we study a powerful yet much less explored way of controlling GANs, that is, to

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