PaLI-X: On Scaling up a Multilingual Vision and Language Model present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture. Our model achieves new
MULTIMODAL AI
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KAFA: Knowledge-Augmented Vision-Language Models for Image Ad Understanding
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KAFA: Rethinking Image Ad Understanding with Knowledge-Augmented Feature Adaptation of Vision-Language Models Image ad understanding is a crucial task with wide real-world applications. Although highly challenging with the involvement of diverse atypical scenes, real-world
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HiFA: Advanced Diffusion Guidance for High-Fidelity Text-to-3D Synthesis
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HiFA: High-fidelity Text-to-3D with Advanced Diffusion Guidance
— AK (@_akhaliq) 31 mai 2023
Automatic text-to-3D synthesis has achieved remarkable advancements through the optimization of 3D models. Existing methods commonly rely on pre-trained text-to-image generative models, such as diffusion models,… pic.twitter.com/Jr3oJkNzFGHiFA: High-fidelity Text-to-3D with Advanced Diffusion Guidance Automatic text-to-3D synthesis has achieved remarkable advancements through the optimization of 3D models. Existing methods commonly rely on pre-trained text-to-image generative models, such as diffusion models,
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StyleAvatar3D: High-Fidelity 3D Avatar Generation Using Diffusion Models
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StyleAvatar3D: Leveraging Image-Text Diffusion Models for High-Fidelity 3D Avatar Generation
— AK (@_akhaliq) 31 mai 2023
present a novel method for generating high-quality, stylized 3D avatars that utilizes pre-trained image-text diffusion models for data generation and a Generative Adversarial Network… pic.twitter.com/mYxICiPCgHStyleAvatar3D: Leveraging Image-Text Diffusion Models for High-Fidelity 3D Avatar Generation present a novel method for generating high-quality, stylized 3D avatars that utilizes pre-trained image-text diffusion models for data generation and a Generative Adversarial Network
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Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation
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Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation propose Make-an-Audio 2, a latent diffusion-based T2A method that builds on the success of Make-an-Audio. Our approach includes several techniques to improve semantic alignment and temporal consistency: Firstly, we use
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Nested Diffusion Processes for Anytime Image Generation
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Nested Diffusion Processes for Anytime Image Generation propose an anytime diffusion-based method that can generate viable images when stopped at arbitrary times before completion. Using existing pretrained diffusion models, we show that the generation scheme can be recomposed
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RIVAL: Diffusion-Based Real-World Image Variation Pipeline
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Real-World Image Variation by Aligning Diffusion Inversion Chain propose a novel inference pipeline called Real-world Image Variation by ALignment (RIVAL) that utilizes diffusion models to generate image variations from a single image exemplar. Our pipeline enhances the
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MindEye reconstructs images from brain activity
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The warm, moist hard drive that is your brain may contain retrievable visual data: MindEye is a novel fMRI-to-image approach to retrieve and reconstruct viewed images from brain activity. Want to learn more? View the project page: https://
medarc-ai.github.io/mindeye/ -
AI Model Draws Thoughts with 80% Accuracy
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Two researchers have created a new #AI model that can draw what you’re thinking with 80% accuracy https://
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AI-Driven Advertising Campaigns Customization Across Digital Platforms
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“The speed of production means that advertising campaigns can be rapidly adapted for different markets or countries…and will be able to create customised advertising for different digital channels such as YouTube or TikTok and their specific user groups.”