401 citations · 880 across the 29 of their papers we have counts for
9 papers · 1 filter
A Three-Level Alignment Framework for Large-Scale 3D Retrieval and Controlled 4D Generation
Philip Xu
We introduce Uni4D, a unified framework for large scale open vocabulary 3D retrieval and controlled 4D generation based on structured three level alignment across text, 3D models,…
UGAE: Unified Geometry and Attribute Enhancement for G-PCC Compressed Point Clouds
Pan Zhao, Hui Yuan, Chongzhen Tian +3
Lossy compression of point clouds reduces storage and transmission costs; however, it inevitably leads to irreversible distortion in geometry structure and attribute information. T…
PC-JND: Subjective Study and Dataset on Just Noticeable Difference for Point Clouds in 6DoF Virtual Reality
Chunling Fan, Yun Zhang, Dietmar Saupe +2
The Just Noticeable Difference (JND) accounts for the minimum distortion at which humans can perceive a difference between a pristine stimulus and its distorted version. The JND co…
STQE: Spatial-Temporal Attribute Quality Enhancement for G-PCC Compressed Dynamic Point Clouds
Tian Guo, Hui Yuan, Xiaolong Mao +3
Very few studies have addressed quality enhancement for compressed dynamic point clouds. In particular, the effective exploitation of spatial-temporal correlations between point cl…
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…
EdgeRegNet: Edge Feature-based Multimodal Registration Network between Images and LiDAR Point Clouds
Yuanchao Yue, Hui Yuan, Qinglong Miao +3
Cross-modal data registration has long been a critical task in computer vision, with extensive applications in autonomous driving and robotics. Accurate and robust registration met…
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…
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…
CS-Net:Contribution-based Sampling Network for Point Cloud Simplification
Tian Guo, Chen Chen, Hui Yuan +3
Point cloud sampling plays a crucial role in reducing computation costs and storage requirements for various vision tasks. Traditional sampling methods, such as farthest point samp…