Point cloud is an explicit representation for 3D objects and scenes, providing precise coordinates and attributes to depict the real world. It lies a solid foundation for wide applications, such as digital entertainment, autonomous driving, remote sensing, robotics, unmanned aerial vehicles, etc. The huge data amount of point clouds motivates the research and development of efficient compression algorithms to relieve the burden of data transmission and storage. Therefore, international industry companies, research institutions and standardization organizations become very interested in devising better compression methods, as well as powerful standards. Moreover, point cloud enhancement algorithms are also very popular, including upsampling, denoising, completion, compression artifacts removal, frame interpolation, etc., which play a critical role in elevating the point cloud quality. Besides the quality evaluation and enhancement for human visual experience, researchers also pay much attention on those for machine analysis tasks. Due to increased efforts on immersive media, embodied artificial intelligence (AI) and unmanned system applications, the 3D vision analysis based on point clouds or point cloud-based multi-modalities is becoming a critical research trend for artificial intelligence. Point cloud technologies can boost the advancements of both the traditional analysis tasks, including classification, segmentation, detection, tracking, etc., and the emerging analysis tasks, including captioning, grounding, task decomposition, question-answering, navigation, etc. The 3D reconstruction and rendering tasks of point clouds have promoted the emergence of 3D Gaussian splatting, which have raised new explorations of 3D visual data compression, reconstruction, generation, rendering, and representation. The advanced algorithms on point cloud compression, enhancement and analysis are solicited, and contributions that advance the state-of-the-art 3D Gaussian splatting technologies for 3D visual data compression, reconstruction, generation, rendering, and representation are also welcomed.

TBD