1 citations · 2 across the 8 of their papers we have counts for
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HyperDiff: Hypergraph Guided Diffusion Model for 3D Human Pose Estimation
Bing Han, Yuhua Huang, Pan Gao
Monocular 3D human pose estimation (HPE) often encounters challenges such as depth ambiguity and occlusion during the 2D-to-3D lifting process. Additionally, traditional methods ma…
Diff-PCC: Diffusion-based Neural Compression for 3D Point Clouds
Kai Liu, Kang You, Pan Gao
Stable diffusion networks have emerged as a groundbreaking development for their ability to produce realistic and detailed visual content. This characteristic renders them ideal de…
Global Attention-Guided Dual-Domain Point Cloud Feature Learning for Classification and Segmentation
Zihao Li, Pan Gao, Kang You +2
Previous studies have demonstrated the effectiveness of point-based neural models on the point cloud analysis task. However, there remains a crucial issue on producing the efficien…
Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes
Kang You, Kai Liu, Li Yu +2
Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces…
Efficient and Generic Point Model for Lossless Point Cloud Attribute Compression
Kang You, Pan Gao, Zhan Ma
The past several years have witnessed the emergence of learned point cloud compression (PCC) techniques. However, current learning-based lossless point cloud attribute compression…
Self-Ensemling for 3D Point Cloud Domain Adaption
Qing Li, Xiaojiang Peng, Chuan Yan +2
Recently 3D point cloud learning has been a hot topic in computer vision and autonomous driving. Due to the fact that it is difficult to manually annotate a qualitative large-scale…