TY - GEN
T1 - TOWARD UNSUPERVISED 3D POINT CLOUD ANOMALY DETECTION USING VARIATIONAL AUTOENCODER
AU - Masuda, Mana
AU - Hachiuma, Ryo
AU - Fujii, Ryo
AU - Saito, Hideo
AU - Sekikawa, Yusuke
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. To the best of our knowledge, this is the first work to tackle the anomaly detection task on a general object represented by a 3D point cloud. We propose a deep variational autoencoder based unsupervised anomaly detection network adapted to the 3D point cloud and an anomaly score specifically for 3D point clouds. To verify the effectiveness of the model, we conducted extensive experiments on ShapeNet dataset. Through quantitative and qualitative evaluation, we demonstrate that the proposed method outperforms the baseline method.
AB - In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. To the best of our knowledge, this is the first work to tackle the anomaly detection task on a general object represented by a 3D point cloud. We propose a deep variational autoencoder based unsupervised anomaly detection network adapted to the 3D point cloud and an anomaly score specifically for 3D point clouds. To verify the effectiveness of the model, we conducted extensive experiments on ShapeNet dataset. Through quantitative and qualitative evaluation, we demonstrate that the proposed method outperforms the baseline method.
KW - 3D point cloud
KW - Anomaly detection
KW - Unsupervised learning
KW - Variational autoencoder
UR - http://www.scopus.com/inward/record.url?scp=85125560969&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125560969&partnerID=8YFLogxK
U2 - 10.1109/ICIP42928.2021.9506795
DO - 10.1109/ICIP42928.2021.9506795
M3 - Conference contribution
AN - SCOPUS:85125560969
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 3118
EP - 3122
BT - 2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
PB - IEEE Computer Society
T2 - 2021 IEEE International Conference on Image Processing, ICIP 2021
Y2 - 19 September 2021 through 22 September 2021
ER -