Author: Daniele Lorenzi

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Daniele Lorenzi received his M.Sc. in ICT for Internet and Multimedia Engineering in 2021 from the University of Padua, Italy. He is a Ph.D. candidate at the Institute of Information Technology (ITEC) at the Alpen-Adria-Universität (AAU) Klagenfurt. He is currently working in the Christian Doppler Laboratory ATHENA and his research interests include adaptive video streaming, immersive media, machine learning, and QoS/QoE evaluation.

Meet P+: A Rich Embeddings Space for Extended Textual Inversion in Text-to-Image Generation

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Text-to-image synthesis refers to the process of generating realistic images from textual prompt descriptions. This technology is a branch of generative models in the...

Meet DreamBooth: An AI Technique For Subject-Driven Text-to-Image Generation

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Imagine your quadruped friend playing outside or your car showcased in an exclusive showroom. Creating these fictional scenarios is particularly challenging, as it requires...

What Can Human Sketches Do for Object Detection? Insights On Sketch-based Image Retrieval

AI Paper Summary
Since prehistoric times, humans have employed sketches to convey and document ideas. Even in the presence of language, their capacity for expressiveness remains unmatched....

Fooling Forensic Classifiers: The Power of Generative Models in Adversarial Face Generation

AI Paper Summary
Recent advancements in Deep Learning (DL), specifically in the field of Generative Adversarial Networks (GAN), have facilitated the generation of highly realistic and diverse...

Explore The Power Of Dynamic Images With Text2Cinemagraph: A Novel AI Tool For Cinemagraphs Generation From Text Prompts

AI Paper Summary
If you are new to the terminology, you may be wondering what cinemagraphs are, but I can assure you that you have probably already...

Meet DISCO: A Novel AI Technique For Human Dance Generation

AI Paper Summary
Generative AI has gained significant interest in the computer vision community. Recent advancements in text-driven image and video synthesis, such as Text-to-Image (T2I) and...

Meet TextDeformer: An AI Framework For Text-guided 3D Mesh Deformation

AI Paper Summary
Three-dimensional (3D) meshes are a primary component of computer graphics and 3D modeling and have several fields of application, including architecture, automotive design, video...

Meet Make-it-3D: An Artificial Intelligence (AI) Framework For High-Fidelity 3D Object Generation From A Single Image

AI Paper Summary
Imagination is a powerful mechanism of humanity. When presented with a single image, humans have the remarkable ability to imagine how the depicted object...

Meet ProFusion: An AI Regularization-Free Framework For Detail Preservation In Text-to-Image Synthesis

AI Paper Summary
The field of text-to-image generation has been extensively explored over the years, and significant progress has been made recently. Researchers have achieved remarkable advancements...

Meet Video-ControlNet: A New Game-Changing Text-to-Video Diffusion Model Shaping the Future of Controllable Video Generation

AI Paper Summary
In recent years, there has been a rapid development in text-based visual content generation. Trained with large-scale image-text pairs, current Text-to-Image (T2I) diffusion models...

Meet CoDi: A Novel Cross-Modal Diffusion Model For Any-to-Any Synthesis

AI Paper Summary
In the past few years, there has been a notable emergence of robust cross-modal models capable of generating one type of information from another,...

Meet MeLoDy: An Efficient Text-to-Audio Diffusion Model For Music Synthesis

AI Paper Summary
Music is an art composed of harmony, melody, and rhythm that permeates every aspect of human life. With the blossoming of deep generative models,...
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