In the realm of speech-driven 3D facial animation, a groundbreaking study has emerged, tackling the challenges of generating realistic and synchronized facial motions from audio inputs. The research, led by Yifan Yang and colleagues from Zhejiang Uni
In the rapidly evolving landscape of digital signal processing, Implicit Neural Representations (INRs) have emerged as a powerful tool for modeling continuous signals such as images, audio, and 3D reconstructions. These representations use multilayer
In the rapidly evolving landscape of digital interaction, a groundbreaking study led by Kevin Qinghong Lin and his team at the University of Adelaide is challenging the conventional design paradigms of Graphical User Interfaces (GUIs). The research i
In the digital age, protecting intellectual property and preventing unauthorized redistribution of digital content is a persistent challenge. Traditional encryption methods like AES, TDES, ECC, and ElGamal offer robust security, but they share a comm
In the realm of speech-driven 3D facial animation, a groundbreaking study has emerged that promises to revolutionize the way we create realistic and synchronized facial motions. The research, spearheaded by a team of experts including Yifan Yang, Zhi
Graph Neural Networks (GNNs) are emerging as a formidable tool in the realm of Intelligent Transportation Systems (ITS), particularly within Vehicular Social Networks (VSNs). A recent survey, conducted by Elham Binshaflout, Aymen Hamrouni, and Hakim
In the rapidly evolving landscape of artificial intelligence, the demand for high-quality, task-centered training data has never been more critical. Multimodal large language models (MLLMs) are being integrated into a wide array of applications, and
In the rapidly evolving landscape of emotional support systems, a groundbreaking framework named MultiMood is set to redefine the standards of trustworthiness and effectiveness. Developed by a team of researchers including Huy M. Le, Dat Tien Nguyen,
In the realm of image classification, the ability to detect out-of-distribution (OOD) samples is paramount, especially in safety-sensitive applications. However, current methods often falter when OOD samples bear a semantic resemblance to the in-dist
In a groundbreaking study, researchers Rolf Bader, Niko Plath, and Patrick Kontopidis have delved into the intricate world of historical musical instruments, specifically a 1755 Dulcken harpsichord housed in the Museum of Applied Arts in Hamburg, Ger
