338 citations · 345 across the 8 of their papers we have counts for
8 papers
SAFT: Sensitivity-Aware Filtering and Transmission for Adaptive 3D Point Cloud Communication over Wireless Channels
Huda Adam Sirag Mekki, Hui Yuan, Mohanad M. G. Hassan +2
Reliable transmission of 3D point clouds over wireless channels is challenging due to time-varying signal-to-noise ratio (SNR) and limited bandwidth. This paper introduces sensitiv…
DUGAE: Unified Geometry and Attribute Enhancement via Spatiotemporal Correlations for G-PCC Compressed Dynamic Point Clouds
Pan Zhao, Hui Yuan, Chang Sun +3
Existing post-decoding quality enhancement methods for point clouds are designed for static data and typically process each frame independently. As a result, they cannot effectivel…
Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation
Zihao Li, Pan Gao, Hui Yuan +2
Discovering inter-point connection for efficient high-dimensional feature extraction from point coordinate is a key challenge in processing point cloud. Most existing methods focus…
GQE-Net: A Graph-based Quality Enhancement Network for Point Cloud Color Attribute
Jinrui Xing, Hui Yuan, Raouf Hamzaoui +2
In recent years, point clouds have become increasingly popular for representing three-dimensional (3D) visual objects and scenes. To efficiently store and transmit point clouds, co…
Dynamic Local Feature Aggregation for Learning on Point Clouds
Zihao Li, Pan Gao, Hui Yuan +1
Existing point cloud learning methods aggregate features from neighbouring points relying on constructing graph in the spatial domain, which results in feature update for each poin…
Progressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds
Qi Liu, Yiyun Liu, Honglei Su +2
With the wide applications of colored point cloud in many fields, point cloud perceptual quality assessment plays a vital role in the visual communication systems owing to the exis…
PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling
Hao Liu, Hui Yuan, Junhui Hou +2
We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficient…
Neural network is heterogeneous: Phase matters more
Yuqi Nie, Hui Yuan
We find a heterogeneity in both complex and real valued neural networks with the insight from wave optics, claiming a much more important role of phase than its amplitude counterpa…