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SotA/Computer Vision/3D Point Cloud Classification/ScanObjectNN

3D Point Cloud Classification on ScanObjectNN

Metric: OBJ_ONLY Accuracy(%) (higher is better)

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#Model↕OBJ_ONLY Accuracy(%)▼Extra DataPaperDate↕Code
1ReCon++65.4YesShapeLLM: Universal 3D Object Understanding for ...2024-02-27Code
2Uni3D65.3YesUni3D: Exploring Unified 3D Representation at Sc...2023-10-10Code
3TAMM-PointBERT (+dlign)60.5YesOpenDlign: Open-World Point Cloud Understanding ...2024-04-25Code
4ViT-Lens60.1YesViT-Lens: Initiating Omni-Modal Exploration thro...2023-08-20Code
5OpenDlign59.5YesOpenDlign: Open-World Point Cloud Understanding ...2024-04-25Code
6MixCon3D-PointBERT58.6YesSculpting Holistic 3D Representation in Contrast...2023-11-03Code
7PointCLIP V250.09YesPointCLIP V2: Prompting CLIP and GPT for Powerfu...2022-11-21Code
8ReCon43.7YesContrast with Reconstruct: Contrastive 3D Repres...2023-02-05Code
9CLIP2Point30.46YesCLIP2Point: Transfer CLIP to Point Cloud Classif...2022-10-03Code
10PointCLIP19.28YesPointCLIP: Point Cloud Understanding by CLIP2021-12-04Code