2 papers
eess.IV2025
MEGA-PCC: A Mamba-based Efficient Approach for Joint Geometry and Attribute Point Cloud Compression
Kai-Hsiang Hsieh, Monyneath Yim, Wen-Hsiao Peng +1
Joint compression of point cloud geometry and attributes is essential for efficient 3D data representation. Existing methods often rely on post-hoc recoloring procedures and manual…
cs.CV2025
SEDD-PCC: A Single Encoder-Dual Decoder Framework For End-To-End Learned Point Cloud Compression
Kai Hsiang Hsieh, Monyneath Yim, Jui Chiu Chiang
To encode point clouds containing both geometry and attributes, most learning-based compression schemes treat geometry and attribute coding separately, employing distinct encoders…