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Can Text-to-Image Generation Be Simplified and Enhanced? This Paper Introduces a Revolutionary Prompt Expansion Framework

Text-to-image generation has evolved significantly, a fascinating intersection of artificial intelligence and creativity. This technology, which transforms textual descriptions into visual content, has broad applications ranging from artistic endeavors to educational tools. Its capability to produce detailed images from text inputs marks a substantial leap in digital content creation, offering a blend of technology and previously unattainable creativity. A primary challenge in this domain has been generating varied and high-quality images from user inputs. Despite…

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Alibaba Announces RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D

In the context of text-to-3D, the key challenge lies in lifting 2D diffusion to 3D generation. The existing methods face difficulties in creating geometry due to the absence of a geometric prior and the intricate interplay of materials and lighting in natural images. To tackle this, a team of researchers from Alibaba have proposed a Normal-Depth diffusion model named RichDreamer, designed to provide a robust geometric foundation for high-fidelity text-to-3D geometry generation. Existing methods have…

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Can Differential Privacy and Federated Learning Protect Your Privacy? This Paper Uncovers a Major Security Flaw in Machine Learning Systems

Federated learning has attracted increasing interest from the research community in the past few years due to its capacity to provide privacy-preserving methods for building machine learning and deep learning models. Sophisticated Artificial Intelligence (AI) solutions have been made possible by utilizing the vast amounts of data currently available in the information technology field in conjunction with the most recent technological developments.  Nonetheless, the dispersed, user-level data production and collecting is one of the fundamental…

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This Paper from Alibaba Unveils DiffusionGAN3D: Revolutionizing 3D Portrait Generation and Adaptation with Advanced GANs and Text-to-Image Diffusion Models

In the rapidly evolving digital imagery and 3D representation landscape, a new milestone is set by the innovative fusion of 3D Generative Adversarial Networks (GANs) with diffusion models. The significance of this development lies in its ability to address longstanding challenges in the field, particularly the scarcity of 3D training data and the complexities associated with the variable geometry and appearance of digital avatars. Traditionally, 3D stylization and avatar creation techniques have leaned heavily on…

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