1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation
Zekai Xu, Kang You, Qinghai Guo +2
Spiking neural networks (SNNs), which mimic biological neural system to convey information via discrete spikes, are well known as brain-inspired models with excellent computing eff…
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…
IPDAE: Improved Patch-Based Deep Autoencoder for Lossy Point Cloud Geometry Compression
Kang You, Pan Gao, Qing Li
Point cloud is a crucial representation of 3D contents, which has been widely used in many areas such as virtual reality, mixed reality, autonomous driving, etc. With the boost of…