Papers with Code 아카이브

3D Object Classification

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하위 태스크: 2
평가표: 4
보존된 평가 기록: 14

3D Object Classification is the task of predicting the class of a 3D object point cloud. It is a voxel level prediction where each voxel is classified into a category. The popular benchmark for this task is the ModelNet dataset. The models for this task are usually evaluated with the Classification Accuracy metric.

Image: Sedaghat et al

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

ModelNet40

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification

평가 기록 7건

Objaverse

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification / Generative 3D Object Classification

평가 기록 7건

ModelNet40

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification / Generative 3D Object Classification

평가 기록 6건

ModelNet10

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification

평가 기록 4건

3R-Scan

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification

평가 기록 2건

Remote Flash LiDAR Vehicles Dataset

원본 태스크: 3D Point Cloud Reconstruction / 3D Point Cloud Classification / 3D Object Classification

평가 기록 1건

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.