Author: Daniele Lorenzi

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.

Learn How to Generate 3D Avatars from 2D Image Collections with this Novel AI Technique

Generative models, such as Generative Adversarial Networks (GANs), have the capacity to generate lifelike images of objects and dressed individuals after being trained on...

This AI Research from China Introduces 4K4D: A 4D Point Cloud Representation that Supports Hardware Rasterization and Enables Unprecedented Rendering Speed

Dynamic view synthesis is a computer vision and graphic task attempting to reconstruct dynamic 3D scenes from captured videos and generate immersive virtual playback....

Unlock Advancing AI Video Understanding with MM-VID for GPT-4V(ision)

Across the globe, individuals create myriad videos daily, including user-generated live streams, video-game live streams, short clips, movies, sports broadcasts, and advertising. As a...

Meet SEINE: a Short-to-Long Video Diffusion Model for High-Quality Extended Videos with Smooth and Creative Transitions Between Scenes

Given the success of diffusion models in text-to-image generation, a surge of video generation techniques has emerged, showcasing interesting applications in this realm. Nevertheless,...

Shedding Light on Cartoon Animation’s Future: AnimeInbet’s Innovation in Line Drawing Inbetweening

Cartoon animation has seen significant progress since its beginnings in the early 1900s when animators would draw individual frames by hand on paper. While...

Meet FreeU: A Novel AI Technique To Enhance Generative Quality Without Additional Training Or Fine-tuning

Probabilistic diffusion models, a cutting-edge category of generative models, have become a critical point in the research landscape, particularly for tasks related to computer...

Meet Decaf: a Novel Artificial Intelligence Monocular Deformation Capture Framework for Face and Hand Interactions

Three-dimensional (3D) tracking from monocular RGB videos is a cutting-edge field in computer vision and artificial intelligence. It focuses on estimating the three-dimensional positions...

Meet POCO: A Novel Artificial Intelligence Framework for 3D Human Pose and Shape Estimation

Estimating 3D Human Pose and Shape (HPS) from photos and moving pictures is necessary to reconstruct human actions in real-world settings. Nevertheless, 3D inference...

AI Researchers from Bytedance and the King Abdullah University of Science and Technology Present a Novel Framework For Animating Hair Blowing in Still Portrait...

Hair is one of the most remarkable features of the human body, impressing with its dynamic qualities that bring scenes to life. Studies have...

Revolutionizing CPR Training With CPR-Coach: Harnessing Artificial Intelligence for Error Recognition and Assessment

Cardiopulmonary Resuscitation (CPR) is a life-saving medical procedure designed to revive individuals who have experienced cardiac arrest, meaning the heart suddenly stops beating effectively...

Meet ReVersion: A Novel AI Diffusion-Based Framework to Address the Relation Inversion Task from Images

Recently, text-to-image (T2I) diffusion models have exhibited promising outcomes, sparking explorations into numerous generative tasks. Some efforts have been made to invert pre-trained text-to-image...

Advancing Image Inpainting: Bridging the Gap Between 2D and 3D Manipulations with this Novel AI Inpainting for Neural Radiance Fields

There has been enduring interest in the manipulation of images due to its wide range of applications in content creation. One of the most...

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