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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
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…