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20182026
most citedReduced Reference Perceptual Quality Model and Application to Rate Control for 3D Point Cloud Compression

401 citations · 880 across the 29 of their papers we have counts for

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16 papers · 1 filter

eess.IV2026

Inter-LPCM: Learning-based Inter-Frame Predictive Coding for LiDAR Point Cloud Compression

Chang Sun, Hui Yuan, Shiqi Jiang +3

Because LiDAR sensors acquire point clouds with a fixed angular resolution, the resulting data can be systematically parameterized and efficiently compressed in the spherical coord…

eess.IV2026

Blind Quality Enhancement for G-PCC Compressed Dynamic Point Clouds

Tian Guo, Hui Yuan, Chang Sun +3

Point cloud compression often introduces noticeable reconstruction artifacts, which makes quality enhancement necessary. Existing approaches typically assume prior knowledge of the…

eess.IV2026

Point Cloud Feature Coding for Object Detection over an Error-Prone Cloud-Edge Collaborative System

Chongzhen Tian, Hui Yuan, Pan Zhao +3

Cloud-edge collaboration enhances machine perception by combining the strengths of edge and cloud computing. Edge devices capture raw data (e.g., 3D point clouds) and extract salie…

eess.IV2025

LPCM: Learning-based Predictive Coding for LiDAR Point Cloud Compression

Chang Sun, Hui Yuan, Shiqi Jiang +3

Since the data volume of LiDAR point clouds is very huge, efficient compression is necessary to reduce their storage and transmission costs. However, existing learning-based compre…

eess.IV2025

PCE-GAN: A Generative Adversarial Network for Point Cloud Attribute Quality Enhancement based on Optimal Transport

Tian Guo, Hui Yuan, Qi Liu +3

Point cloud compression significantly reduces data volume but sacrifices reconstruction quality, highlighting the need for advanced quality enhancement techniques. Most existing ap…

eess.IV2025

Interleaved Block-based Learned Image Compression with Feature Enhancement and Quantization Error Compensation

Shiqi Jiang, Hui Yuan, Shuai Li +3

In recent years, learned image compression (LIC) methods have achieved significant performance improvements. However, obtaining a more compact latent representation and reducing th…

eess.IV2024

SPAC: Sampling-based Progressive Attribute Compression for Dense Point Clouds

Xiaolong Mao, Hui Yuan, Tian Guo +3

We propose an end-to-end attribute compression method for dense point clouds. The proposed method combines a frequency sampling module, an adaptive scale feature extraction module…

eess.IV2024★ 1 cited

Feature Compression for Cloud-Edge Multimodal 3D Object Detection

Chongzhen Tian, Zhengxin Li, Hui Yuan +3

Machine vision systems, which can efficiently manage extensive visual perception tasks, are becoming increasingly popular in industrial production and daily life. Due to the challe…

eess.IV2024

3DAttGAN: A 3D Attention-based Generative Adversarial Network for Joint Space-Time Video Super-Resolution

Congrui Fu, Hui Yuan, Liquan Shen +2

In many applications, including surveillance, entertainment, and restoration, there is a need to increase both the spatial resolution and the frame rate of a video sequence. The ai…

eess.IV2024

PCAC-GAN: A Sparse-Tensor-Based Generative Adversarial Network for 3D Point Cloud Attribute Compression

Xiaolong Mao, Hui Yuan, Xin Lu +2

Learning-based methods have proven successful in compressing geometric information for point clouds. For attribute compression, however, they still lag behind non-learning-based me…

eess.IV2024★ 17 cited

Enhancing octree-based context models for point cloud geometry compression with attention-based child node number prediction

Chang Sun, Hui Yuan, Xiaolong Mao +2

In point cloud geometry compression, most octreebased context models use the cross-entropy between the onehot encoding of node occupancy and the probability distribution predicted…

eess.IV2024★ 19 cited

Enhancing context models for point cloud geometry compression with context feature residuals and multi-loss

Chang Sun, Hui Yuan, Shuai Li +2

In point cloud geometry compression, context models usually use the one-hot encoding of node occupancy as the label, and the cross-entropy between the one-hot encoding and the prob…

eess.IV2024

Global Spatial-Temporal Information-based Residual ConvLSTM for Video Space-Time Super-Resolution

Congrui Fu, Hui Yuan, Shiqi Jiang +3

By converting low-frame-rate, low-resolution videos into high-frame-rate, high-resolution ones, space-time video super-resolution techniques can enhance visual experiences and faci…

eess.IV2023

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…

eess.IV2020★ 401 cited

Reduced Reference Perceptual Quality Model and Application to Rate Control for 3D Point Cloud Compression

Qi Liu, Hui Yuan, Raouf Hamzaoui +3

In rate-distortion optimization, the encoder settings are determined by maximizing a reconstruction quality measure subject to a constraint on the bit rate. One of the main challen…

eess.IV2020★ 66 cited

Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression

Qi Liu, Hui Yuan, Junhui Hou +2

Rate distortion optimization plays a very important role in image/video coding. But for 3D point cloud, this problem has not been investigated. In this paper, the rate and distorti…