| cff-version: 1.2.0 |
| type: dataset |
| title: "FLKD 3D Benchmark: Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification" |
| authors: |
| - family-names: "Aiersilan" |
| given-names: "Aizierjiang" |
| version: 1.0.0 |
| date-released: 2026-06-29 |
| description: "Pre-trained models and experimental results from the comprehensive benchmark evaluating 13 Federated Learning algorithms, 11 Knowledge Distillation objectives, and their combinations on 3D point cloud classification tasks, specifically on the Craniosynostosis medical dataset. This collection includes model checkpoints, training logs, metrics, and configurations for reproducible research in federated learning and knowledge distillation for 3D deep learning." |
| keywords: |
| - federated-learning |
| - knowledge-distillation |
| - point-cloud |
| - 3d-classification |
| - benchmarking |
| - deep-learning |
| - privacy-preserving-ml |
| - distributed-training |
| license: MIT |
| repository-code: "https://github.com/Ezharjan/FLKD3DBenchmark" |
| url: "https://ezharjan.github.io/FLKD3DBenchmark" |
| references: |
| - type: conference-paper |
| authors: |
| - family-names: "Aiersilan" |
| given-names: "Aizierjiang" |
| title: "Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification" |
| conference: |
| name: "European Conference on Computer Vision" |
| acronym: "ECCV" |
| year: 2026 |
| publisher: |
| name: "Springer" |
| doi: "10.1007/XXX-X-XXX-XXXXX-X" |
| contact: |
| - type: person |
| name: "Aizierjiang Aiersilan" |
| email: "alx.laboratory@gmail.com" |
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