HyperAI超神経
ホームニュース最新論文チュートリアルデータセット百科事典SOTALLMモデルGPU ランキング学会
検索
サイトについて
HyperAI超神経

3D Anomaly Detection And Segmentation On

評価指標

Detection AUROC
Segmentation AUPRO

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
Detection AUROC
Segmentation AUPRO
Paper TitleRepository
Voxel GAN0.5370.583The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
Voxel VM0.5710.492The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection (FPFH)0.7820.924Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection
Shape-Guided (only SDF)0.9160.931Shape-Guided: Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
CPMF (2D)0.89180.9145Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection
Voxel AE0.6990.348The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization
3D-ST_128-0.833Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors-
CPMF (2D+3D)0.95150.9293Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection
CPMF (3D)0.83040.9230Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection
0 of 9 row(s) selected.