A Systematic Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation

In three linesSystematic survey of deep learning architectures for 3D point cloud classification and segmentation. Addresses challenges (unordered nature, sensor noise, occlusions) and strategies (format conversion, local geometry extraction, permutation-invariant processing, self-attention). Evaluates models on standard benchmarks.

Summary generated by Claude — human-verified