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Published at November 21

Point Cloud Denoising With Fine-Granularity Dynamic Graph Convolutional Networks

cs.CV

Released Date: November 21, 2024

Authors: Wenqiang Xu¹, Wenrui Dai¹, Duoduo Xue¹, Ziyang Zheng¹, Chenglin Li¹, Junni Zou¹, Hongkai Xiong¹

Aff.: ¹Institution not specified

Arxiv: http://arxiv.org/abs/2411.14158v1

Refer to caption

	10K (Sprase)								30K (Dense)
noise	0.01		0.015		0.02		0.03		0.01		0.015		0.02		0.03
Model	CD	EMD	CD	EMD	CD	EMD	CD	EMD	CD	EMD	CD	EMD	CD	EMD	CD	EMD
GF	10.99	2.27	11.01	2.35	11.66	2.57	16.78	3.77	2.95	2.20	4.84	3.35	8.21	5.53	18.03	12.32
GLR	5.42	1.05	6.91	1.43	9.88	2.12	11.90	2.70	2.58	1.76	4.07	2.90	8.74	5.95	16.22	11.49
PCN	8.07	1.80	12.90	2.77	19.56	4.21	41.46	8.97	3.65	2.36	6.76	4.46	12.29	8.23	33.43	22.23
DGCNN	7.70	1.95	8.58	2.45	17.86	4.27	19.32	4.88	3.19	2.52	3.95	3.22	4.85	4.02	8.09	6.72
GPD	6.57	1.31	11.07	2.54	21.06	4.32	41.06	8.72	2.17	1.57	9.17	6.14	17.60	11.35	36.42	23.93
TD	10.94	2.61	15.81	3.59	22.28	4.96	40.17	8.71	3.20	2.41	5.89	4.04	11.59	7.67	28.52	18.95
DMR	11.19	2.66	12.92	2.97	13.70	3.34	17.43	4.65	4.39	3.65	4.91	4.10	5.77	4.51	8.25	6.80
ScoreNet	6.71	2.13	8.02	2.46	9.53	2.85	16.63	4.39	2.64	2.15	4.25	3.59	5.19	4.25	11.30	7.92
Deeprs	6.02	1.21	8.84	1.76	10.87	2.21	15.78	3.31	3.70	2.37	5.23	3.48	7.26	4.74	14.19	8.76
PathNet	9.99	2.16	12.82	2.75	12.98	2.88	19.11	4.26	8.14	5.49	8.45	6.34	9.66	7.17	14.70	10.75
Proposed	4.39	0.90	6.44	1.37	8.45	1.84	13.44	3.40	2.04	1.46	2.82	2.08	3.93	2.93	7.72	6.67