timzhang642/3D-Machine-Learning

Curated collection of research papers, datasets, and courses spanning 3D object classification, detection, pose estimation, geometry synthesis, and scene understanding—organized by 3D representation types (point clouds, meshes, volumetric, multi-view). Covers deep learning approaches alongside traditional geometric methods, with references to foundational datasets like ModelNet, ShapeNet, and PASCAL3D+ that enable benchmarking across different 3D data modalities. Functions as a living research index with community contributions via pull requests and an associated Slack workspace for collaborative knowledge sharing.

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