Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …

Recent studies have indicated that foundation models, such as BERT and GPT, excel at
adapting to various downstream tasks. This adaptability has made them a dominant force in …

Point cloud completion concerns to predict missing part for incomplete 3D shapes. A
common strategy is to generate complete shape according to incomplete input. However …

The task of point cloud completion aims to predict the missing part for an incomplete 3D
shape. A widely used strategy is to generate a complete point cloud from the incomplete …

Limited training data is a long-standing problem for video emotion analysis (VEA). Existing
works leverage the power of large-scale image datasets for transferring while failing to …

In this paper, we present a novel unpaired point cloud completion network, named
Cycle4Completion, to infer the complete geometries from a partial 3D object. Previous …

As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing
DNNs become more complex and diverse, ranging from improving a conventional model …

In recent years, road traffic accidents, as a leading cause of accidental deaths, have been
attracting more and more attention across several disciplines. Notably, the feature study on …

Developing effective visual analytics systems demands care in characterization of domain
problems and integration of visualization techniques and computational models. Urban …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …