High-res multi-view results

This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

Accuracy [%]: The fraction of the reconstruction which is closer to the ground truth than the evaluation threshold distance (*). Larger is better.
Completeness [%]: The fraction of the ground truth which is closer to the reconstruction than the evaluation threshold distance (*). Larger is better.
F₁ score [%]: The harmonic mean of accuracy and completeness, used to rank methods based on both metrics. Larger is better.
Time [s]: The runtime of the method. Smaller is better.

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.

Method	all	high-res multi-view	indoor	outdoor	botani.	boulde.	bridge	door	exhibi.	lectur.	living.	lounge	observ.	old co.	statue	terrac.

DeepPCF-MVS	69.37 1	80.65 13	81.56 11	77.94 105	85.46 70	49.56 246	90.99 21	86.66 97	70.58 34	80.07 33	95.30 2	56.18 29	90.97 101	82.57 36	86.22 37	93.28 14

IB-MVS	68.87 2	74.01 127	72.03 153	79.94 43	83.04 127	55.50 56	90.24 25	88.65 47	67.14 81	61.38 254	81.74 294	53.21 47	94.28 23	60.45 235	62.41 315	90.03 142
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
DeepC-MVS_fast	67.50 3	78.00 39	77.63 39	79.13 55	88.52 29	55.12 73	89.95 28	85.98 113	68.31 59	71.33 117	92.75 47	45.52 147	90.37 120	71.15 137	85.14 47	91.91 53
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS	67.15 4	76.90 58	76.27 65	78.80 65	80.70 208	55.02 78	86.39 112	86.71 95	66.96 89	67.91 158	89.97 120	48.03 89	91.41 79	75.60 89	84.14 59	89.96 144
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HY-MVS	67.03 5	73.90 130	73.14 128	76.18 162	84.70 83	47.36 326	75.56 369	86.36 105	66.27 100	70.66 133	83.91 247	51.05 61	89.31 162	67.10 168	72.61 204	91.88 55

3Dnovator	64.70 6	74.46 119	72.48 137	80.41 31	82.84 138	55.40 62	83.08 251	88.61 52	67.61 76	59.85 269	88.66 144	34.57 320	93.97 26	58.42 253	88.70 12	91.85 57

3Dnovator+	62.71 7	72.29 166	70.50 178	77.65 113	83.40 115	51.29 198	87.32 84	86.40 104	59.01 256	58.49 304	88.32 159	32.40 344	91.27 83	57.04 273	82.15 73	90.38 123

PVSNet	62.49 8	69.27 235	67.81 237	73.64 254	84.41 89	51.85 180	84.63 196	77.80 335	66.42 97	59.80 270	84.95 232	22.14 424	80.44 383	55.03 293	75.11 175	88.62 185

ACMP	61.11 9	66.24 307	64.33 308	72.00 306	74.89 346	49.12 259	83.18 247	79.83 284	55.41 332	52.29 374	82.68 271	25.83 394	86.10 304	60.89 226	63.94 295	80.78 361
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PCF-MVS	61.03 10	70.10 214	68.40 220	75.22 204	77.15 302	51.99 175	79.30 345	82.12 229	56.47 316	61.88 250	86.48 206	43.98 170	87.24 264	55.37 292	72.79 201	86.43 249
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
OpenMVS	61.00 11	69.99 219	67.55 242	77.30 124	78.37 276	54.07 120	84.36 203	85.76 118	57.22 294	56.71 335	87.67 185	30.79 363	92.83 42	43.04 377	84.06 61	85.01 275

ACMM	58.35 12	64.35 323	62.01 329	71.38 321	74.21 356	48.51 281	82.25 274	79.66 288	47.61 397	54.54 356	80.11 310	25.26 399	86.00 310	51.26 326	63.16 307	79.64 374
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PVSNet_0	57.04 13	61.19 354	57.24 367	73.02 269	77.45 293	50.31 229	79.43 344	77.36 345	63.96 147	47.51 413	72.45 401	25.03 402	83.78 348	52.76 315	19.22 487	84.96 277

TAPA-MVS	56.12 14	61.82 351	60.18 350	66.71 381	78.48 274	37.97 430	75.19 374	76.41 362	46.82 403	57.04 330	86.52 205	27.67 382	77.03 418	26.50 453	67.02 263	85.14 273
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMH+	54.58 15	58.55 377	55.24 381	68.50 366	74.68 348	45.80 362	80.27 326	70.21 422	47.15 401	42.77 435	75.48 371	16.73 454	85.98 312	35.10 416	54.78 387	73.72 434

ACMH	53.70 16	59.78 360	55.94 379	71.28 322	76.59 310	48.35 287	80.15 330	76.11 363	49.74 382	41.91 438	73.45 391	16.50 455	90.31 123	31.42 430	57.63 363	75.17 422
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OpenMVS_ROB	53.19 17	59.20 365	56.00 378	68.83 357	71.13 395	44.30 376	83.64 227	75.02 373	46.42 407	46.48 420	73.03 393	18.69 441	88.14 220	27.74 448	61.80 318	74.05 432

PLC	52.38 18	60.89 355	58.97 359	66.68 383	81.77 166	45.70 363	78.96 348	74.04 385	43.66 429	47.63 410	83.19 263	23.52 414	77.78 413	37.47 394	60.46 327	76.55 412
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
LTVRE_ROB	45.45 19	52.73 408	49.74 412	61.69 420	69.78 416	34.99 436	44.52 475	67.60 436	43.11 432	43.79 428	74.03 380	18.54 443	81.45 368	28.39 445	57.94 357	68.62 456
Andreas Kuhn, Heiko HirschmÃ¼ller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
COLMAP_ROB	43.60 20	50.90 420	48.05 421	59.47 429	67.81 431	40.57 418	71.25 411	62.72 452	36.49 453	36.19 459	73.51 389	13.48 460	73.92 437	20.71 469	50.26 409	63.92 467
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CMPMVS	40.41 21	55.34 395	52.64 398	63.46 407	60.88 460	43.84 383	61.58 450	71.06 417	30.43 468	36.33 458	74.63 376	24.14 410	75.44 430	48.05 349	66.62 266	71.12 452
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PMVS	19.57 22	25.07 455	22.43 460	32.99 472	23.12 503	22.98 478	40.98 480	35.19 487	15.99 485	11.95 494	35.87 486	1.47 499	49.29 481	5.41 497	31.90 469	26.70 491
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVE	16.60 23	17.34 463	13.39 466	29.16 475	28.43 499	19.72 487	13.73 493	23.63 498	7.23 496	7.96 496	21.41 492	0.80 501	36.08 492	6.97 492	10.39 493	31.69 488
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
gbinet_0.2-2-1-0.02		64.20 324	61.39 334	72.63 284	70.85 398	46.32 349	85.92 127	85.98 113	55.27 334	51.88 380	72.29 408	33.14 335	87.82 234	48.50 345	48.72 417	83.73 304

0.3-1-1-0.015		72.75 153	71.06 168	77.81 107	80.58 213	50.62 212	89.45 37	88.60 53	63.74 153	65.56 184	81.82 292	46.61 116	90.64 111	62.86 209	60.35 328	92.17 42

0.4-1-1-0.1		72.39 160	70.70 173	77.46 119	80.45 219	50.04 234	89.09 47	88.45 58	63.06 169	64.91 197	81.60 297	45.98 132	90.46 117	62.40 212	60.34 330	91.88 55

0.4-1-1-0.2		72.79 152	71.07 167	77.94 105	80.58 213	50.83 208	89.59 35	88.63 49	63.94 148	65.74 182	81.80 293	46.05 128	90.68 107	62.98 208	60.35 328	92.31 38

wanda-best-256-512		64.87 317	62.23 323	72.81 276	70.49 404	46.85 333	85.71 143	85.71 119	56.85 299	51.25 383	72.31 405	36.16 292	87.84 232	52.67 317	48.90 413	83.73 304

usedtu_dtu_shiyan2		50.47 421	46.43 428	62.61 414	51.66 475	31.70 456	75.62 368	75.65 367	36.36 454	34.89 463	56.91 468	12.01 462	78.40 400	30.87 434	43.86 440	77.72 397

usedtu_dtu_shiyan1		69.05 238	67.91 228	72.46 291	75.40 335	46.24 352	85.74 139	86.80 91	65.23 125	58.75 296	80.31 307	40.90 217	86.83 277	53.29 304	64.77 284	84.31 286

blended_shiyan8		64.70 319	62.04 327	72.69 281	70.33 408	46.62 339	85.48 154	85.66 121	56.58 313	50.94 390	72.18 409	35.81 302	87.80 238	52.47 320	48.91 412	83.65 313

E5new		75.74 93	74.80 101	78.57 79	79.85 233	54.93 84	85.87 128	84.72 171	70.19 39	70.90 125	87.74 180	45.97 135	89.71 144	72.15 131	75.79 158	91.06 97

FE-blended-shiyan7		64.87 317	62.23 323	72.81 276	70.49 404	46.85 333	85.71 143	85.71 119	56.85 299	51.25 383	72.31 405	36.16 292	87.84 232	52.67 317	48.90 413	83.73 304

E6new		75.74 93	74.80 101	78.56 81	79.85 233	54.92 89	85.87 128	84.72 171	70.19 39	70.90 125	87.73 182	45.98 132	89.71 144	72.16 129	75.78 161	91.06 97

blended_shiyan6		64.70 319	62.04 327	72.69 281	70.34 407	46.60 341	85.48 154	85.65 123	56.59 312	50.91 391	72.18 409	35.82 301	87.81 235	52.46 321	48.90 413	83.66 312

usedtu_blend_shiyan5		63.62 332	60.36 347	73.40 262	70.49 404	47.96 307	79.13 347	80.68 263	47.51 399	51.25 383	72.31 405	36.16 292	88.50 204	56.81 275	48.90 413	83.73 304

blend_shiyan4		67.33 282	65.28 295	73.45 261	70.71 399	47.96 307	86.21 118	85.65 123	56.45 317	52.18 377	72.99 394	45.89 137	88.50 204	56.81 275	60.68 326	83.90 301

E6		75.74 93	74.80 101	78.56 81	79.85 233	54.92 89	85.87 128	84.72 171	70.19 39	70.90 125	87.73 182	45.98 132	89.71 144	72.16 129	75.78 161	91.06 97

E5		75.74 93	74.80 101	78.57 79	79.85 233	54.93 84	85.87 128	84.72 171	70.19 39	70.90 125	87.74 180	45.97 135	89.71 144	72.15 131	75.79 158	91.06 97

FE-MVSNET3		69.05 238	67.91 228	72.46 291	75.39 336	46.24 352	85.74 139	86.80 91	65.23 125	58.75 296	80.31 307	40.90 217	86.83 277	53.29 304	64.77 284	84.31 286

E4		75.99 82	75.16 89	78.48 86	79.56 241	54.74 98	86.66 109	84.80 166	70.62 32	71.16 122	87.90 175	46.84 110	89.47 158	72.70 124	76.20 152	91.23 88

E3new		76.85 60	76.24 66	78.66 71	81.62 176	55.01 79	86.94 97	85.10 152	71.55 22	71.93 104	88.61 149	48.40 84	89.60 151	74.50 100	77.53 128	91.36 79

FE-MVSNET2		58.78 373	56.44 373	65.82 388	63.57 452	38.92 424	79.59 339	81.75 244	56.14 321	43.06 434	68.15 431	25.22 400	80.64 378	42.29 383	48.16 420	77.91 394

fmvsm_s_conf0.5_n_11		76.28 74	76.81 56	74.71 218	79.21 251	46.90 332	85.03 176	73.96 386	69.00 55	79.70 37	93.88 12	48.07 87	87.71 245	84.26 21	78.15 119	89.50 157

E2		76.39 71	75.67 75	78.56 81	80.49 216	54.87 94	86.80 104	84.95 158	71.09 28	71.51 112	88.21 163	47.55 97	89.53 154	73.65 113	76.77 139	91.29 84

MED-MVS test				80.14 38	84.34 91	54.93 84	87.61 72	87.22 81	57.43 289	81.85 18	92.88 42		93.75 30	80.19 52	85.13 48	91.76 61

MED-MVS		79.53 21	79.33 19	80.14 38	84.34 91	54.93 84	87.61 72	87.22 81	56.62 309	81.85 18	92.88 42	58.11 20	93.75 30	80.19 52	85.13 48	91.76 61

E3		76.39 71	75.67 75	78.56 81	80.49 216	54.87 94	86.80 104	84.95 158	71.09 28	71.51 112	88.21 163	47.55 97	89.53 154	73.65 113	76.77 139	91.29 84

TestfortrainingZip a		79.20 24	78.77 26	80.49 26	84.34 91	55.96 51	87.61 72	87.22 81	57.43 289	81.85 18	92.88 42	58.11 20	93.75 30	74.37 102	85.13 48	91.75 64

TestfortrainingZip				83.28 1	90.91 7	58.80 9	87.61 72	91.34 10	56.28 320	88.36 1	95.55 1	65.41 5	96.39 4		88.20 15	94.63 3

fmvsm_s_conf0.5_n_10		76.80 61	76.81 56	76.78 148	78.91 261	47.85 312	83.44 235	74.66 377	68.93 56	81.31 24	94.12 7	47.44 101	90.82 104	83.43 28	79.06 110	91.66 66

viewdifsd2359ckpt07		74.81 116	74.01 116	77.21 130	79.62 239	53.13 146	85.70 146	83.75 199	68.12 62	68.14 156	87.33 192	46.51 120	87.92 228	73.32 118	73.63 190	90.57 116

viewdifsd2359ckpt09		74.92 113	73.70 120	78.60 78	80.28 225	54.94 83	84.77 189	80.56 268	69.96 45	69.38 142	88.38 154	46.01 131	90.50 116	72.44 126	71.49 218	90.38 123

viewdifsd2359ckpt13		75.96 83	75.07 91	78.65 73	81.14 192	55.21 68	86.15 120	84.95 158	69.98 43	70.49 138	88.16 165	46.10 126	89.86 136	72.39 127	76.23 151	90.89 107

viewcassd2359sk11		76.66 66	76.01 72	78.62 74	81.14 192	54.95 82	86.88 101	85.04 154	71.37 26	71.76 106	88.44 152	48.02 90	89.57 153	74.17 106	77.23 130	91.33 83

viewdifsd2359ckpt11		70.68 202	69.10 210	75.40 190	75.33 338	50.85 206	81.57 298	78.00 330	66.99 87	64.96 195	85.52 220	39.52 235	86.81 279	68.86 155	61.15 323	88.56 188

viewmacassd2359aftdt		75.91 86	75.14 90	78.21 97	79.40 245	54.82 96	86.71 107	84.98 156	70.89 31	71.52 111	87.89 176	45.43 149	88.85 189	72.35 128	77.08 132	90.97 104

viewmsd2359difaftdt		70.68 202	69.10 210	75.40 190	75.33 338	50.85 206	81.57 298	78.00 330	66.99 87	64.96 195	85.52 220	39.52 235	86.81 279	68.86 155	61.16 322	88.56 188

diffmvs_AUTHOR		74.80 117	74.30 110	76.29 155	77.34 295	53.19 142	83.17 248	79.50 293	69.93 46	71.55 110	88.57 150	45.85 140	86.03 309	77.17 78	75.64 165	89.67 149

FE-MVSNET		51.43 417	48.22 419	61.06 425	60.78 461	32.48 452	73.85 386	64.62 443	46.30 412	37.47 456	66.27 437	20.80 430	77.38 416	23.43 461	40.48 449	73.31 438

fmvsm_l_conf0.5_n_9		77.10 52	77.48 43	75.98 169	77.54 291	47.77 317	86.35 114	73.46 397	68.69 57	81.07 26	94.40 5	49.06 82	88.89 185	87.39 8	79.32 106	91.27 87

mamba_0408		66.33 304	62.87 315	76.70 150	80.45 219	51.81 183	46.11 473	78.90 307	55.46 330	63.82 220	84.54 235	31.91 353	91.03 92	55.68 288	68.97 246	87.25 224

icg_test_0407_2		71.26 188	69.99 193	75.09 206	82.26 151	50.87 202	79.65 338	85.16 145	62.91 173	63.68 224	86.07 208	35.56 304	84.32 341	64.03 197	70.55 230	90.09 136

SSM_04072		64.04 327	62.87 315	67.56 371	80.45 219	51.81 183	46.11 473	78.90 307	55.46 330	63.82 220	84.54 235	31.91 353	63.62 459	55.68 288	68.97 246	87.25 224

SSM_0407		69.71 224	67.38 247	76.69 151	80.45 219	51.81 183	81.36 306	80.18 274	54.07 348	63.82 220	85.05 228	33.09 336	91.01 95	59.40 240	68.97 246	87.25 224

viewmambaseed2359dif		73.51 140	72.78 133	75.71 177	76.93 306	51.89 179	82.81 257	79.66 288	65.46 115	70.29 139	88.05 170	45.55 145	85.85 317	73.49 116	72.76 202	89.39 160

IMVS_0407		71.97 173	70.10 191	77.57 114	82.26 151	50.87 202	80.69 320	85.16 145	62.91 173	63.68 224	86.07 208	35.56 304	91.75 71	64.03 197	70.55 230	90.09 136

viewmanbaseed2359cas		76.71 65	76.16 68	78.37 94	81.16 191	55.05 77	86.96 96	85.32 134	71.71 19	72.25 99	88.50 151	46.86 109	88.96 180	74.55 99	78.08 120	91.08 95

IMVS_0404		69.11 236	67.25 251	74.68 219	82.26 151	50.87 202	76.74 362	85.16 145	62.91 173	50.76 394	86.07 208	26.76 387	83.06 358	64.03 197	70.55 230	90.09 136

SSM_0404		70.13 211	67.87 235	76.88 142	80.22 226	52.00 174	81.71 292	80.18 274	54.07 348	65.36 187	85.05 228	33.09 336	91.03 92	59.40 240	71.80 213	87.63 214

IMVS_0403		72.39 160	70.59 177	77.79 108	82.26 151	50.87 202	81.76 287	85.16 145	62.91 173	64.87 198	86.07 208	37.71 258	92.40 55	64.03 197	70.55 230	90.09 136

SD_0403		65.51 315	65.18 298	66.48 385	78.37 276	29.94 464	74.64 379	78.55 320	66.47 96	54.87 351	84.35 241	38.20 249	82.47 360	38.90 391	72.30 209	87.05 229

fmvsm_s_conf0.5_n_9		76.66 66	76.94 53	75.85 172	79.54 242	48.30 292	82.63 262	71.84 406	70.25 38	80.63 30	94.53 3	50.78 68	87.42 258	88.32 5	73.92 188	91.82 59

ME-MVS		79.48 22	79.20 22	80.35 32	88.96 27	54.93 84	88.65 53	88.50 57	56.62 309	79.87 35	92.88 42	51.96 55	94.36 22	80.19 52	85.13 48	91.76 61

NormalMVS		77.09 53	77.02 50	77.32 123	81.66 173	52.32 166	89.31 42	82.11 230	72.20 14	73.23 82	91.05 83	46.52 118	91.00 96	76.23 82	80.83 83	88.64 182

lecture		74.14 125	73.05 131	77.44 120	81.66 173	50.39 222	87.43 80	84.22 190	51.38 371	72.10 100	90.95 92	38.31 248	93.23 37	70.51 140	80.83 83	88.69 180

SymmetryMVS		77.43 48	77.09 49	78.44 90	82.56 146	52.32 166	89.31 42	84.15 191	72.20 14	73.23 82	91.05 83	46.52 118	91.00 96	76.23 82	78.55 114	92.00 51

Elysia		65.59 312	62.65 318	74.42 225	69.85 414	49.46 253	80.04 331	82.11 230	46.32 410	58.74 298	79.64 316	20.30 432	88.57 200	55.48 290	71.37 219	85.22 271

StellarMVS		65.59 312	62.65 318	74.42 225	69.85 414	49.46 253	80.04 331	82.11 230	46.32 410	58.74 298	79.64 316	20.30 432	88.57 200	55.48 290	71.37 219	85.22 271

KinetiMVS		71.15 189	69.25 207	76.82 143	77.99 281	50.49 217	85.05 174	86.51 100	59.78 233	64.10 212	85.34 223	32.16 347	91.33 82	58.82 247	73.54 192	88.64 182

LuminaMVS		66.60 300	64.37 307	73.27 267	70.06 413	49.57 243	80.77 318	81.76 243	50.81 374	60.56 263	78.41 331	24.50 407	87.26 263	64.24 195	68.25 252	82.99 325

VortexMVS		68.49 253	66.84 256	73.46 260	81.10 196	48.75 273	84.63 196	84.73 170	62.05 191	57.22 329	77.08 349	34.54 322	89.20 169	63.08 205	57.12 366	82.43 333

AstraMVS		70.12 212	68.56 215	74.81 215	76.48 311	47.48 322	84.35 204	82.58 224	63.80 150	62.09 247	84.54 235	31.39 359	89.96 133	68.24 162	63.58 298	87.00 230

guyue		70.53 206	69.12 208	74.76 217	77.61 287	47.53 320	84.86 186	85.17 143	62.70 180	62.18 243	83.74 250	34.72 316	89.86 136	64.69 193	66.38 271	86.87 233

sc_t1		53.51 406	49.92 411	64.29 400	70.33 408	39.55 422	72.93 393	59.60 456	38.74 443	47.16 415	66.47 436	17.59 448	76.50 424	36.83 402	39.62 452	76.82 405

tt0320-xc		52.22 414	48.38 418	63.75 404	72.19 383	42.25 405	72.19 404	57.59 459	37.24 448	44.41 425	61.56 453	17.90 446	75.89 428	35.60 408	36.73 457	73.12 442

tt0320		52.45 411	48.75 415	63.55 405	71.47 390	41.85 406	72.42 399	59.73 455	36.33 455	44.52 424	61.55 454	19.34 437	76.45 425	33.53 420	39.85 451	72.36 444

fmvsm_s_conf0.5_n_8		76.50 69	76.68 60	75.94 170	78.67 266	47.92 310	85.18 167	74.71 376	68.09 63	80.67 29	94.26 6	47.09 106	89.26 164	86.62 10	74.85 180	90.65 112

fmvsm_s_conf0.5_n_7		73.10 146	73.89 119	70.72 332	74.17 357	46.03 356	83.28 243	74.19 381	67.10 82	73.94 73	91.73 71	43.42 184	77.61 414	83.92 26	73.26 194	88.53 191

fmvsm_s_conf0.5_n_6		76.17 77	76.84 55	74.15 236	77.42 294	46.46 343	85.53 153	77.86 334	69.78 48	79.78 36	92.90 41	46.80 111	84.81 335	84.67 19	76.86 138	91.17 92

fmvsm_s_conf0.5_n_5		75.02 110	75.07 91	74.88 213	74.33 355	47.83 314	83.99 217	73.54 392	67.10 82	76.32 56	92.43 54	45.42 150	86.35 297	82.98 31	79.50 105	90.47 121

fmvsm_s_conf0.5_n_4		74.92 113	74.88 97	75.03 208	75.96 326	47.53 320	85.84 132	73.19 399	67.07 84	79.43 39	92.60 51	46.12 124	88.03 226	84.70 18	69.01 244	89.53 155

SSC-MVS3.2		68.13 262	66.89 254	71.85 315	82.26 151	43.97 381	82.09 278	89.29 29	71.74 17	61.12 257	79.83 315	34.60 319	87.45 256	41.23 384	59.85 334	84.14 289

testing3-2		72.30 165	72.35 140	72.15 300	83.07 125	47.64 318	85.46 156	89.81 25	66.17 103	61.96 249	84.88 234	58.93 13	82.27 361	55.87 284	64.97 282	86.54 244

myMVS_eth3d28		77.77 42	77.94 34	77.27 126	87.58 44	52.89 154	86.06 123	91.33 11	74.15 7	68.16 155	88.24 161	58.17 19	88.31 215	69.88 146	77.87 122	90.61 115

UWE-MVS-28		67.43 277	67.98 227	65.75 389	75.66 331	34.74 438	80.00 334	88.17 62	64.21 138	57.27 327	84.14 244	45.68 144	78.82 398	44.33 370	72.40 206	83.70 309

fmvsm_l_conf0.5_n_3		75.73 97	75.78 73	75.61 180	76.03 323	48.33 290	85.34 157	72.92 400	67.16 80	78.55 44	93.85 15	46.22 122	87.53 254	85.61 14	76.30 149	90.98 103

fmvsm_s_conf0.5_n_3		74.97 112	75.42 83	73.62 256	76.99 304	46.67 337	83.13 249	71.14 415	66.20 102	82.13 14	93.76 17	47.49 99	84.00 344	81.95 40	76.02 153	90.19 133

fmvsm_s_conf0.5_n_2		72.02 171	71.72 155	72.92 272	76.79 308	45.90 357	84.48 200	66.11 439	64.26 136	76.12 57	93.40 26	36.26 290	86.04 308	81.47 45	66.54 269	86.82 240

fmvsm_s_conf0.1_n_2		71.45 185	71.01 169	72.78 278	75.37 337	45.82 361	84.18 210	64.59 445	64.02 142	75.67 58	93.02 39	34.99 314	85.99 311	81.18 49	66.04 277	86.52 246

GDP-MVS		75.27 103	74.38 108	77.95 104	79.04 256	52.86 155	85.22 164	86.19 109	62.43 187	70.66 133	90.40 107	53.51 45	91.60 74	69.25 150	72.68 203	89.39 160

BP-MVS1		76.09 79	75.55 79	77.71 111	79.49 243	52.27 170	84.70 191	90.49 19	64.44 132	69.86 141	90.31 109	55.05 37	91.35 80	70.07 144	75.58 167	89.53 155

reproduce_monomvs		69.71 224	68.52 217	73.29 266	86.43 55	48.21 295	83.91 220	86.17 110	68.02 68	54.91 350	77.46 341	42.96 191	88.86 186	68.44 158	48.38 419	82.80 330

mmtdpeth		57.93 381	54.78 385	67.39 374	72.32 380	43.38 389	72.72 395	68.93 430	54.45 345	56.85 332	62.43 450	17.02 451	83.46 353	57.95 262	30.31 472	75.31 420

reproduce_model		71.07 193	69.67 198	75.28 201	81.51 185	48.82 271	81.73 290	80.57 267	47.81 395	68.26 153	90.78 97	36.49 288	88.60 196	65.12 190	74.76 181	88.42 195

reproduce-ours		71.77 180	70.43 180	75.78 174	81.96 160	49.54 249	82.54 267	81.01 257	48.77 389	69.21 144	90.96 89	37.13 274	89.40 159	66.28 174	76.01 154	88.39 196

our_new_method		71.77 180	70.43 180	75.78 174	81.96 160	49.54 249	82.54 267	81.01 257	48.77 389	69.21 144	90.96 89	37.13 274	89.40 159	66.28 174	76.01 154	88.39 196

mmdepth		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

monomultidepth		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

mvs5depth		50.97 419	46.98 425	62.95 411	56.63 467	34.23 442	62.73 446	67.35 437	45.03 420	48.00 407	65.41 443	10.40 468	79.88 393	36.00 405	31.27 471	74.73 427

MVStest1		38.35 439	34.53 445	49.82 451	51.43 476	30.41 458	50.39 468	55.25 461	17.56 483	26.45 481	65.85 441	11.72 463	57.00 473	14.79 481	17.31 489	62.05 470

ttmdpeth		40.58 437	37.50 441	49.85 450	49.40 480	22.71 480	56.65 461	46.78 469	28.35 470	40.29 447	69.42 426	5.35 485	61.86 462	20.16 471	21.06 485	64.96 465

WBMVS		73.93 129	73.39 122	75.55 184	87.82 41	55.21 68	89.37 39	87.29 79	67.27 78	63.70 223	80.30 309	60.32 7	86.47 291	61.58 221	62.85 312	84.97 276

dongtai		43.51 433	44.07 434	41.82 460	63.75 450	21.90 483	63.80 438	72.05 405	39.59 439	33.35 470	54.54 470	41.04 214	57.30 472	10.75 487	17.77 488	46.26 482

kuosan		50.20 423	50.09 408	50.52 449	73.09 369	29.09 470	65.25 432	74.89 374	48.27 392	41.34 441	60.85 458	43.45 183	67.48 456	18.59 476	25.07 479	55.01 474

MVSMamba_PlusPlus		75.28 102	73.39 122	80.96 22	80.85 204	58.25 11	74.47 380	87.61 76	50.53 376	65.24 188	83.41 258	57.38 23	92.83 42	73.92 110	87.13 22	91.80 60

MGCFI-Net		74.07 126	74.64 106	72.34 296	82.90 134	43.33 391	80.04 331	79.96 280	65.61 113	74.93 62	91.85 68	48.01 91	80.86 374	71.41 135	77.10 131	92.84 25

testing91		78.30 35	77.54 41	80.61 24	88.16 37	57.12 26	87.94 66	91.07 16	71.43 23	70.75 130	88.04 172	55.82 31	92.65 48	69.61 147	75.00 178	92.05 47

testing11		79.18 25	78.85 25	80.16 36	88.33 32	56.99 27	88.31 58	92.06 1	72.82 11	70.62 135	88.37 155	57.69 22	92.30 57	75.25 94	76.24 150	91.20 90

testing99		78.45 29	77.78 38	80.45 30	88.28 35	56.81 33	87.95 65	91.49 6	71.72 18	70.84 129	88.09 167	57.29 24	92.63 50	69.24 151	75.13 174	91.91 53

UBG		78.86 27	78.86 24	78.86 63	87.80 42	55.43 58	87.67 70	91.21 12	72.83 10	72.10 100	88.40 153	58.53 18	89.08 171	73.21 122	77.98 121	92.08 44

UWE-MVS		72.17 169	72.15 147	72.21 298	82.26 151	44.29 377	86.83 103	89.58 26	65.58 114	65.82 179	85.06 227	45.02 156	84.35 340	54.07 299	75.18 171	87.99 206

ETVMVS		75.80 92	75.44 82	76.89 141	86.23 57	50.38 224	85.55 151	91.42 7	71.30 27	68.80 149	87.94 174	56.42 28	89.24 165	56.54 278	74.75 182	91.07 96

sasdasda		78.17 36	77.86 36	79.12 56	84.30 94	54.22 113	87.71 68	84.57 179	67.70 74	77.70 48	92.11 61	50.90 63	89.95 134	78.18 71	77.54 126	93.20 16

testing222		77.70 44	77.22 47	79.14 54	86.95 48	54.89 93	87.18 90	91.96 2	72.29 13	71.17 121	88.70 143	55.19 33	91.24 85	65.18 189	76.32 148	91.29 84

WB-MVSnew		69.36 234	68.24 223	72.72 280	79.26 250	49.40 255	85.72 142	88.85 41	61.33 205	64.59 204	82.38 280	34.57 320	87.53 254	46.82 358	70.63 227	81.22 357

fmvsm_l_conf0.5_n_a		75.88 87	76.07 70	75.31 196	76.08 320	48.34 288	85.24 163	70.62 419	63.13 168	81.45 23	93.62 22	49.98 75	87.40 260	87.76 7	76.77 139	90.20 131

fmvsm_l_conf0.5_n		75.95 84	76.16 68	75.31 196	76.01 325	48.44 285	84.98 179	71.08 416	63.50 160	81.70 22	93.52 23	50.00 73	87.18 265	87.80 6	76.87 137	90.32 126

fmvsm_s_conf0.1_n_a		72.82 151	72.05 151	75.12 205	70.95 397	47.97 305	82.72 259	68.43 433	62.52 184	78.17 46	93.08 37	44.21 169	88.86 186	84.82 17	63.54 299	88.54 190

fmvsm_s_conf0.1_n		73.80 132	73.26 125	75.43 189	73.28 366	47.80 315	84.57 199	69.43 428	63.34 163	78.40 45	93.29 31	44.73 166	89.22 167	85.99 12	66.28 275	89.26 163

fmvsm_s_conf0.5_n_a		73.68 137	73.15 126	75.29 199	75.45 334	48.05 302	83.88 222	68.84 431	63.43 162	78.60 42	93.37 29	45.32 151	88.92 184	85.39 15	64.04 292	88.89 174

fmvsm_s_conf0.5_n		74.48 118	74.12 112	75.56 183	76.96 305	47.85 312	85.32 161	69.80 426	64.16 140	78.74 41	93.48 24	45.51 148	89.29 163	86.48 11	66.62 266	89.55 153

MM		82.69 2	83.29 3	80.89 23	84.38 90	55.40 62	92.16 10	89.85 24	75.28 4	82.41 12	93.86 14	54.30 40	93.98 25	90.29 1	87.13 22	93.30 13

WAC-MVS						34.28 440								22.56 464

Syy-MVS		61.51 352	61.35 336	62.00 417	81.73 167	30.09 461	80.97 312	81.02 255	60.93 216	55.06 348	82.64 272	35.09 311	80.81 375	16.40 480	58.32 348	75.10 424

test_fmvsmconf0.1_n		73.69 136	73.15 126	75.34 194	70.71 399	48.26 293	82.15 275	71.83 407	66.75 91	74.47 69	92.59 52	44.89 160	87.78 242	83.59 27	71.35 221	89.97 143

test_fmvsmconf0.01_n		71.97 173	70.95 171	75.04 207	66.21 434	47.87 311	80.35 325	70.08 423	65.85 112	72.69 90	91.68 74	39.99 231	87.67 247	82.03 39	69.66 240	89.58 152

myMVS_eth3d		63.52 333	63.56 314	63.40 408	81.73 167	34.28 440	80.97 312	81.02 255	60.93 216	55.06 348	82.64 272	48.00 93	80.81 375	23.42 463	58.32 348	75.10 424

testing3		59.97 359	60.19 349	59.32 430	77.60 288	30.01 463	81.75 289	81.79 240	53.54 352	50.34 395	79.94 311	48.99 83	76.91 419	17.19 478	50.59 408	71.03 453

SSC-MVS		35.20 444	34.30 446	37.90 465	52.58 472	8.65 503	61.86 447	41.64 478	31.81 466	25.54 482	52.94 475	23.39 415	59.28 469	6.10 495	12.86 491	45.78 484

test_fmvsmconf_n		74.41 120	74.05 114	75.49 188	74.16 358	48.38 286	82.66 260	72.57 401	67.05 86	75.11 61	92.88 42	46.35 121	87.81 235	83.93 25	71.71 214	90.28 127

WB-MVS		37.41 442	36.37 442	40.54 463	54.23 470	10.43 500	65.29 431	43.75 474	34.86 461	27.81 479	54.63 469	24.94 403	63.21 460	6.81 494	15.00 490	47.98 481

test_fmvsmvis_n_1920		71.29 187	70.38 183	74.00 241	71.04 396	48.79 272	79.19 346	64.62 443	62.75 178	66.73 164	91.99 65	40.94 215	88.35 211	83.00 30	73.18 195	84.85 280

dmvs_re		67.61 271	66.00 276	72.42 293	81.86 164	43.45 387	64.67 436	80.00 278	69.56 52	60.07 267	85.00 231	34.71 317	87.63 249	51.48 325	66.68 264	86.17 253

SDMVSNet		71.89 175	70.62 176	75.70 178	81.70 169	51.61 188	73.89 384	88.72 46	66.58 92	61.64 252	82.38 280	37.63 259	89.48 156	77.44 76	65.60 279	86.01 254

dmvs_testset		57.65 382	58.21 362	55.97 441	74.62 349	9.82 501	63.75 439	63.34 449	67.23 79	48.89 402	83.68 255	39.12 240	76.14 426	23.43 461	59.80 335	81.96 338

sd_testset		67.79 268	65.95 278	73.32 263	81.70 169	46.33 348	68.99 421	80.30 272	66.58 92	61.64 252	82.38 280	30.45 365	87.63 249	55.86 285	65.60 279	86.01 254

test_fmvsm_n_1920		75.56 99	75.54 80	75.61 180	74.60 350	49.51 251	81.82 286	74.08 383	66.52 95	80.40 31	93.46 25	46.95 107	89.72 143	86.69 9	75.30 169	87.61 215

test_cas_vis1_n_1920		67.10 288	66.60 264	68.59 364	65.17 442	43.23 392	83.23 245	69.84 425	55.34 333	70.67 132	87.71 184	24.70 406	76.66 423	78.57 66	64.20 291	85.89 260

test_vis1_n_1920		68.59 252	68.31 221	69.44 351	69.16 420	41.51 410	84.63 196	68.58 432	58.80 260	73.26 81	88.37 155	25.30 398	80.60 380	79.10 59	67.55 259	86.23 252

test_vis1_n		51.19 418	49.66 413	55.76 442	51.26 477	29.85 465	67.20 429	38.86 481	32.12 465	59.50 277	79.86 313	8.78 474	58.23 471	56.95 274	52.46 403	79.19 376

test_fmvs1_n		52.55 410	51.19 404	56.65 438	51.90 474	30.14 460	67.66 426	42.84 476	32.27 464	62.30 242	82.02 290	9.12 473	60.84 463	57.82 265	54.75 389	78.99 377

mvsany_test1		43.38 434	42.57 436	45.82 455	50.96 478	26.10 475	55.80 462	27.74 494	27.15 472	47.41 414	74.39 378	18.67 442	44.95 486	44.66 368	36.31 458	66.40 461

APD_test1		26.46 454	24.41 455	32.62 473	37.58 489	21.74 484	40.50 481	30.39 491	11.45 490	16.33 487	43.76 479	1.63 498	41.62 488	11.24 485	26.82 477	34.51 487

test_vis1_rt		40.29 438	38.64 439	45.25 457	48.91 483	30.09 461	59.44 455	27.07 495	24.52 476	38.48 453	51.67 476	6.71 480	49.44 480	44.33 370	46.59 434	56.23 472

test_vis3_rt		24.79 456	22.95 459	30.31 474	28.59 498	18.92 489	37.43 484	17.27 502	12.90 487	21.28 485	29.92 491	1.02 500	36.35 491	28.28 446	29.82 475	35.65 485

test_fmvs2		45.89 430	44.32 432	50.62 448	45.85 486	24.70 477	58.87 458	37.84 484	25.22 474	52.46 373	74.56 377	7.07 477	54.69 475	49.28 339	47.70 424	72.48 443

test_fmvs1		53.60 405	52.54 400	56.78 437	58.07 463	30.26 459	68.95 422	42.19 477	32.46 463	63.59 228	82.56 276	11.55 464	60.81 464	58.25 256	55.27 383	79.28 375

test_fmvs3		37.95 441	35.75 443	44.55 458	35.50 492	18.92 489	48.32 469	34.00 489	18.36 482	41.31 443	61.58 452	2.29 493	48.06 484	42.72 380	37.71 456	66.66 460

mvsany_test3		28.00 450	25.98 452	34.05 469	28.97 497	15.31 495	34.54 486	18.17 500	16.24 484	29.30 476	53.37 474	2.79 491	33.38 497	30.01 436	20.41 486	53.45 476

testf1		21.11 458	19.08 462	27.18 476	30.56 494	18.28 491	33.43 487	24.48 496	8.02 494	12.02 492	33.50 488	0.75 502	35.09 494	7.68 490	21.32 482	28.17 489

APD_test2		21.11 458	19.08 462	27.18 476	30.56 494	18.28 491	33.43 487	24.48 496	8.02 494	12.02 492	33.50 488	0.75 502	35.09 494	7.68 490	21.32 482	28.17 489

test_f		27.12 452	24.85 453	33.93 470	26.17 502	15.25 496	30.24 490	22.38 499	12.53 489	28.23 477	49.43 477	2.59 492	34.34 496	25.12 456	26.99 476	52.20 477

FE-MVS		64.15 325	60.43 346	75.30 198	80.85 204	49.86 239	68.28 425	78.37 324	50.26 380	59.31 281	73.79 383	26.19 392	91.92 68	40.19 387	66.67 265	84.12 290

FA-MVS(test-final)		69.00 242	66.60 264	76.19 161	83.48 111	47.96 307	74.73 376	82.07 233	57.27 293	62.18 243	78.47 330	36.09 296	92.89 40	53.76 303	71.32 222	87.73 211

balanced_conf03		80.28 16	79.73 15	81.90 12	86.47 54	59.34 6	80.45 322	89.51 27	69.76 49	71.05 123	86.66 202	58.68 17	93.24 36	84.64 20	90.40 6	93.14 19

MonoMVSNet		66.80 297	64.41 306	73.96 242	76.21 318	48.07 301	76.56 365	78.26 326	64.34 134	54.32 359	74.02 381	37.21 272	86.36 296	64.85 192	53.96 393	87.45 219

patch_mono-2		80.84 12	81.59 10	78.62 74	90.34 10	53.77 123	88.08 60	88.36 60	76.17 2	79.40 40	91.09 82	55.43 32	90.09 130	85.01 16	80.40 90	91.99 52

EGC-MVSNET		33.75 446	30.42 450	43.75 459	64.94 445	36.21 435	60.47 454	40.70 480	0.02 500	0.10 501	53.79 472	7.39 476	60.26 465	11.09 486	35.23 462	34.79 486

test2506		72.91 149	72.43 139	74.32 231	80.12 229	44.18 380	83.19 246	84.77 168	64.02 142	65.97 176	87.43 189	47.67 96	88.72 191	59.08 243	79.66 102	90.08 140

test1111		71.06 194	70.42 182	72.97 271	79.48 244	41.49 411	84.82 188	82.74 221	64.20 139	62.98 234	87.43 189	35.20 309	87.92 228	58.54 250	78.42 116	89.49 158

ECVR-MVS		71.81 177	71.00 170	74.26 233	80.12 229	43.49 386	84.69 192	82.16 227	64.02 142	64.64 201	87.43 189	35.04 312	89.21 168	61.24 224	79.66 102	90.08 140

test_blank		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

tt0805		63.39 335	61.31 337	69.64 348	69.36 418	38.87 425	78.00 354	85.48 125	48.82 388	55.66 347	81.66 295	24.38 408	86.37 295	49.04 341	59.36 340	83.68 310

DVP-MVS++		82.44 3	82.38 6	82.62 5	91.77 4	57.49 18	84.98 179	88.88 38	58.00 273	83.60 7	93.39 27	67.21 2	96.39 4	81.64 43	91.98 4	93.98 6

FOURS1					83.24 119	49.90 238	84.98 179	78.76 313	47.71 396	73.42 78

MSC_two_6792asdad				81.53 16	91.77 4	56.03 48		91.10 13					96.22 9	81.46 46	86.80 29	92.34 36

PC_three_1452									66.58 92	87.27 3	93.70 18	66.82 4	94.95 18	89.74 4	91.98 4	93.98 6

No_MVS				81.53 16	91.77 4	56.03 48		91.10 13					96.22 9	81.46 46	86.80 29	92.34 36

test_one_0601					89.39 23	57.29 23		88.09 64	57.21 295	82.06 15	93.39 27	54.94 39

eth-test2					0.00 507

eth-test					0.00 507

GeoE		69.96 220	67.88 232	76.22 158	81.11 195	51.71 187	84.15 211	76.74 356	59.83 232	60.91 258	84.38 239	41.56 210	88.10 223	51.67 324	70.57 229	88.84 176

test_method		24.09 457	21.07 461	33.16 471	27.67 500	8.35 505	26.63 491	35.11 488	3.40 497	14.35 489	36.98 483	3.46 490	35.31 493	19.08 475	22.95 481	55.81 473

Anonymous20240521		51.65 415	48.42 417	61.34 424	56.43 468	39.65 421	73.57 388	73.47 396	36.64 452	36.59 457	63.98 446	10.75 467	72.25 447	35.35 410	49.01 411	72.11 446

h-mvs33		73.95 128	72.89 132	77.15 131	80.17 228	50.37 225	84.68 193	83.33 207	68.08 64	71.97 102	88.65 147	42.50 194	91.15 89	78.82 62	57.78 362	89.91 146

hse-mvs2		71.44 186	70.68 174	73.73 252	76.34 313	47.44 325	79.45 343	79.47 295	68.08 64	71.97 102	86.01 214	42.50 194	86.93 274	78.82 62	53.46 400	86.83 239

CL-MVSNet_self_test		62.98 339	61.14 339	68.50 366	65.86 437	42.96 394	84.37 202	82.98 217	60.98 214	53.95 363	72.70 398	40.43 224	83.71 349	41.10 385	47.93 423	78.83 380

KD-MVS_2432*1600		59.04 369	56.44 373	66.86 379	79.07 254	45.87 359	72.13 405	80.42 270	55.03 337	48.15 405	71.01 416	36.73 282	78.05 406	35.21 412	30.18 473	76.67 407

KD-MVS_self_test		49.24 424	46.85 426	56.44 439	54.32 469	22.87 479	57.39 459	73.36 398	44.36 425	37.98 454	59.30 463	18.97 440	71.17 449	33.48 421	42.44 444	75.26 421

AUN-MVS		68.20 261	66.35 267	73.76 250	76.37 312	47.45 324	79.52 342	79.52 292	60.98 214	62.34 240	86.02 212	36.59 287	86.94 273	62.32 214	53.47 399	86.89 232

ZD-MVS					89.55 15	53.46 129		84.38 182	57.02 297	73.97 72	91.03 85	44.57 167	91.17 88	75.41 93	81.78 77

SR-MVS-dyc-post		68.27 259	66.87 255	72.48 290	80.96 199	48.14 298	81.54 300	76.98 350	46.42 407	62.75 237	89.42 129	31.17 361	86.09 306	60.52 233	72.06 211	83.19 321

RE-MVS-def			66.66 262		80.96 199	48.14 298	81.54 300	76.98 350	46.42 407	62.75 237	89.42 129	29.28 372		60.52 233	72.06 211	83.19 321

SED-MVS		81.92 8	81.75 9	82.44 8	89.48 18	56.89 30	92.48 3	88.94 36	57.50 287	84.61 5	94.09 8	58.81 14	96.37 7	82.28 37	87.60 19	94.06 4

IU-MVS					89.48 18	57.49 18		91.38 9	66.22 101	88.26 2				82.83 32	87.60 19	92.44 33

OPU-MVS				81.71 14	92.05 3	55.97 50	92.48 3				94.01 10	67.21 2	95.10 16	89.82 3	92.55 3	94.06 4

test_241102_TWO								88.76 45	57.50 287	83.60 7	94.09 8	56.14 30	96.37 7	82.28 37	87.43 21	92.55 31

test_241102_ONE					89.48 18	56.89 30		88.94 36	57.53 285	84.61 5	93.29 31	58.81 14	96.45 1

SF-MVS		77.64 45	77.42 44	78.32 95	83.75 107	52.47 162	86.63 110	87.80 68	58.78 261	74.63 65	92.38 55	47.75 95	91.35 80	78.18 71	86.85 28	91.15 93

cl22		68.85 243	67.69 238	72.35 295	78.07 280	49.98 236	82.45 271	78.48 322	62.50 185	58.46 305	77.95 333	49.99 74	85.17 328	62.55 211	58.72 344	81.90 339

miper_ehance_all_eth		68.70 251	67.58 240	72.08 302	76.91 307	49.48 252	82.47 270	78.45 323	62.68 181	58.28 309	77.88 335	50.90 63	85.01 332	61.91 218	58.72 344	81.75 341

miper_enhance_ethall		69.77 223	68.90 213	72.38 294	78.93 260	49.91 237	83.29 242	78.85 309	64.90 128	59.37 279	79.46 319	52.77 49	85.16 329	63.78 201	58.72 344	82.08 336

ZNCC-MVS		75.82 91	75.02 94	78.23 96	83.88 105	53.80 122	86.91 100	86.05 112	59.71 235	67.85 159	90.55 100	42.23 198	91.02 94	72.66 125	85.29 46	89.87 147

dcpmvs_2		79.33 23	78.94 23	80.49 26	89.75 13	56.54 38	84.83 187	83.68 201	67.85 70	69.36 143	90.24 110	60.20 9	92.10 65	84.14 23	80.40 90	92.82 26

cl____		67.43 277	65.93 279	71.95 310	76.33 314	48.02 303	82.58 263	79.12 304	61.30 207	56.72 334	76.92 352	46.12 124	86.44 293	57.98 260	56.31 371	81.38 352

DIV-MVS_self_test		67.43 277	65.93 279	71.94 311	76.33 314	48.01 304	82.57 264	79.11 305	61.31 206	56.73 333	76.92 352	46.09 127	86.43 294	57.98 260	56.31 371	81.39 351

eth_miper_zixun_eth		66.98 293	65.28 295	72.06 303	75.61 332	50.40 221	81.00 311	76.97 353	62.00 192	56.99 331	76.97 350	44.84 162	85.58 319	58.75 248	54.42 390	80.21 369

9.14			78.19 31		85.67 64		88.32 57	88.84 42	59.89 231	74.58 67	92.62 50	46.80 111	92.66 47	81.40 48	85.62 42

uanet_test		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

DCPMVS		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

save fliter					85.35 72	56.34 43	89.31 42	81.46 247	61.55 201

ET-MVSNet_ETH3D		75.23 106	74.08 113	78.67 70	84.52 87	55.59 54	88.92 49	89.21 32	68.06 67	53.13 369	90.22 112	49.71 78	87.62 251	72.12 133	70.82 226	92.82 26

UniMVSNet_ETH3D		62.51 344	60.49 344	68.57 365	68.30 428	40.88 417	73.89 384	79.93 282	51.81 368	54.77 353	79.61 318	24.80 404	81.10 370	49.93 333	61.35 320	83.73 304

EIA-MVS		75.92 85	75.18 88	78.13 99	85.14 76	51.60 189	87.17 91	85.32 134	64.69 130	68.56 151	90.53 101	45.79 141	91.58 75	67.21 167	82.18 72	91.20 90

miper_refine_blended		59.04 369	56.44 373	66.86 379	79.07 254	45.87 359	72.13 405	80.42 270	55.03 337	48.15 405	71.01 416	36.73 282	78.05 406	35.21 412	30.18 473	76.67 407

miper_lstm_enhance		63.91 328	62.30 322	68.75 360	75.06 343	46.78 335	69.02 420	81.14 253	59.68 237	52.76 371	72.39 402	40.71 221	77.99 408	56.81 275	53.09 401	81.48 347

ETV-MVS		77.17 51	76.74 58	78.48 86	81.80 165	54.55 108	86.13 121	85.33 133	68.20 61	73.10 84	90.52 102	45.23 153	90.66 109	79.37 57	80.95 80	90.22 129

CS-MVS		76.77 62	76.70 59	76.99 137	83.55 109	48.75 273	88.60 54	85.18 142	66.38 98	72.47 95	91.62 76	45.53 146	90.99 100	74.48 101	82.51 68	91.23 88

D2MVS		63.49 334	61.39 334	69.77 347	69.29 419	48.93 267	78.89 349	77.71 338	60.64 223	49.70 397	72.10 413	27.08 385	83.48 352	54.48 297	62.65 313	76.90 404

DVP-MVS		81.30 10	81.00 13	82.20 9	89.40 21	57.45 20	92.34 5	89.99 22	57.71 281	81.91 16	93.64 20	55.17 34	96.44 2	81.68 41	87.13 22	92.72 29
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD									58.00 273	81.91 16	93.64 20	56.54 26	96.44 2	81.64 43	86.86 27	92.23 39

test_0728_SECOND				82.20 9	89.50 16	57.73 14	92.34 5	88.88 38					96.39 4	81.68 41	87.13 22	92.47 32

test0726					89.40 21	57.45 20	92.32 7	88.63 49	57.71 281	83.14 10	93.96 11	55.17 34

SR-MVS		70.92 198	69.73 197	74.50 222	83.38 116	50.48 219	84.27 207	79.35 300	48.96 387	66.57 170	90.45 103	33.65 331	87.11 267	66.42 171	74.56 183	85.91 259

DPM-MVS		82.39 4	82.36 7	82.49 6	80.12 229	59.50 5	92.24 8	90.72 17	69.37 53	83.22 9	94.47 4	63.81 6	93.18 38	74.02 108	93.25 2	94.80 1

GST-MVS		74.87 115	73.90 117	77.77 109	83.30 117	53.45 131	85.75 137	85.29 137	59.22 248	66.50 171	89.85 122	40.94 215	90.76 105	70.94 138	83.35 63	89.10 170

test_yl		75.85 88	74.83 99	78.91 60	88.08 39	51.94 176	91.30 17	89.28 30	57.91 275	71.19 119	89.20 134	42.03 203	92.77 44	69.41 148	75.07 176	92.01 49

thisisatest0530		70.47 209	68.56 215	76.20 160	79.78 237	51.52 192	83.49 234	88.58 55	57.62 284	58.60 300	82.79 266	51.03 62	91.48 77	52.84 311	62.36 317	85.59 267

Anonymous20240529		69.71 224	67.28 249	77.00 136	83.78 106	50.36 226	88.87 51	85.10 152	47.22 400	64.03 214	83.37 259	27.93 378	92.10 65	57.78 267	67.44 260	88.53 191

Anonymous202405211		70.11 213	67.88 232	76.79 147	87.20 47	47.24 329	89.49 36	77.38 344	54.88 340	66.14 173	86.84 198	20.93 429	91.54 76	56.45 282	71.62 215	91.59 69

DCV-MVSNet		75.85 88	74.83 99	78.91 60	88.08 39	51.94 176	91.30 17	89.28 30	57.91 275	71.19 119	89.20 134	42.03 203	92.77 44	69.41 148	75.07 176	92.01 49

tttt0517		68.33 257	66.29 269	74.46 223	78.08 279	49.06 260	80.88 315	89.08 34	54.40 346	54.75 354	80.77 304	51.31 59	90.33 122	49.35 338	58.01 356	83.99 295

our_test_3		59.11 367	55.08 384	71.18 326	71.42 391	53.29 140	81.96 280	74.52 378	48.32 391	42.08 436	69.28 428	28.14 375	82.15 363	34.35 418	45.68 437	78.11 393

thisisatest0515		73.64 138	72.20 145	77.97 102	81.63 175	53.01 150	86.69 108	88.81 43	62.53 183	64.06 213	85.65 216	52.15 54	92.50 52	58.43 251	69.84 238	88.39 196

ppachtmachnet_test		58.56 376	54.34 386	71.24 323	71.42 391	54.74 98	81.84 285	72.27 403	49.02 386	45.86 423	68.99 429	26.27 390	83.30 355	30.12 435	43.23 443	75.69 416

SMA-MVS		79.10 26	78.76 27	80.12 40	84.42 88	55.87 52	87.58 79	86.76 94	61.48 204	80.26 32	93.10 34	46.53 117	92.41 54	79.97 55	88.77 11	92.08 44
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
GSMVS																88.13 202

DPE-MVS		79.82 19	79.66 17	80.29 33	89.27 25	55.08 76	88.70 52	87.92 67	55.55 328	81.21 25	93.69 19	56.51 27	94.27 24	78.36 68	85.70 41	91.51 74
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					89.33 24	55.48 57				82.27 13

thres100view900		66.87 295	65.42 293	71.24 323	83.29 118	43.15 393	81.67 293	87.78 69	59.04 255	55.92 343	82.18 286	43.73 175	87.80 238	28.80 440	66.36 272	82.78 331

tfpnnormal		61.47 353	59.09 357	68.62 363	76.29 317	41.69 407	81.14 309	85.16 145	54.48 344	51.32 382	73.63 388	32.32 345	86.89 276	21.78 467	55.71 381	77.29 402

tfpn200view9		67.57 273	66.13 273	71.89 314	84.05 100	45.07 368	83.40 238	87.71 74	60.79 219	57.79 314	82.76 267	43.53 180	87.80 238	28.80 440	66.36 272	82.78 331

c3_l		67.97 263	66.66 262	71.91 313	76.20 319	49.31 257	82.13 277	78.00 330	61.99 193	57.64 318	76.94 351	49.41 79	84.93 333	60.62 230	57.01 367	81.49 345

CHOSEN 280x420		57.53 384	56.38 376	60.97 426	74.01 359	48.10 300	46.30 472	54.31 464	48.18 394	50.88 392	77.43 343	38.37 247	59.16 470	54.83 294	63.14 308	75.66 417

CANet		80.90 11	81.17 12	80.09 42	87.62 43	54.21 115	91.60 14	86.47 102	73.13 9	79.89 34	93.10 34	49.88 77	92.98 39	84.09 24	84.75 55	93.08 20

Fast-Effi-MVS+-dtu		66.53 301	64.10 311	73.84 247	72.41 378	52.30 169	84.73 190	75.66 366	59.51 239	56.34 340	79.11 325	28.11 376	85.85 317	57.74 268	63.29 304	83.35 315

Effi-MVS+-dtu		66.24 307	64.96 302	70.08 343	75.17 340	49.64 242	82.01 279	74.48 379	62.15 189	57.83 312	76.08 367	30.59 364	83.79 347	65.40 187	60.93 325	76.81 406

CANet_DTU		73.71 135	73.14 128	75.40 190	82.61 145	50.05 233	84.67 195	79.36 299	69.72 50	75.39 59	90.03 119	29.41 370	85.93 316	67.99 163	79.11 108	90.22 129

MGCNet		82.10 7	82.64 4	80.47 29	86.63 52	54.69 103	92.20 9	86.66 97	74.48 5	82.63 11	93.80 16	50.83 67	93.70 33	90.11 2	86.44 34	93.01 22

MP-MVS-pluss		75.54 100	75.03 93	77.04 133	81.37 188	52.65 159	84.34 205	84.46 181	61.16 208	69.14 146	91.76 70	39.98 232	88.99 178	78.19 69	84.89 54	89.48 159
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		82.30 6	83.47 1	78.80 65	82.99 130	52.71 157	85.04 175	88.63 49	66.08 107	86.77 4	92.75 47	72.05 1	91.46 78	83.35 29	93.53 1	92.23 39
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
sam_mvs1												38.86 243				88.13 202

sam_mvs												35.99 300

IterMVS-SCA-FT		59.12 366	58.81 360	60.08 428	70.68 403	45.07 368	80.42 324	74.25 380	43.54 430	50.02 396	73.73 384	31.97 350	56.74 474	51.06 329	53.60 397	78.42 387

TSAR-MVS + MP.		78.31 34	78.26 29	78.48 86	81.33 189	56.31 44	81.59 297	86.41 103	69.61 51	81.72 21	88.16 165	55.09 36	88.04 225	74.12 107	86.31 35	91.09 94
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xiu_mvs_v1_base_debu		71.60 182	70.29 186	75.55 184	77.26 298	53.15 143	85.34 157	79.37 296	55.83 324	72.54 91	90.19 113	22.38 420	86.66 285	73.28 119	76.39 144	86.85 236

OPM-MVS		70.75 201	69.58 199	74.26 233	75.55 333	51.34 196	86.05 124	83.29 211	61.94 195	62.95 235	85.77 215	34.15 325	88.44 207	65.44 186	71.07 223	82.99 325
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		76.43 70	75.66 77	78.73 67	81.92 162	54.67 105	84.06 215	85.35 132	61.10 211	72.99 85	91.50 79	40.25 225	91.00 96	76.84 80	86.98 26	90.51 120

ambc				62.06 416	53.98 471	29.38 468	35.08 485	79.65 290		41.37 440	59.96 460	6.27 483	82.15 363	35.34 411	38.22 455	74.65 428

MTGPA								81.31 250

SPE-MVS-test		77.20 50	77.25 46	77.05 132	84.60 85	49.04 263	89.42 38	85.83 117	65.90 111	72.85 88	91.98 67	45.10 154	91.27 83	75.02 96	84.56 56	90.84 108

Effi-MVS+		75.24 105	73.61 121	80.16 36	81.92 162	57.42 22	85.21 165	76.71 357	60.68 222	73.32 80	89.34 131	47.30 102	91.63 73	68.28 160	79.72 101	91.42 76

xiu_mvs_v2_base		79.86 18	79.31 20	81.53 16	85.03 79	60.73 4	91.65 13	86.86 90	70.30 37	80.77 27	93.07 38	37.63 259	92.28 59	82.73 34	85.71 40	91.57 71

xiu_mvs_v1_base		71.60 182	70.29 186	75.55 184	77.26 298	53.15 143	85.34 157	79.37 296	55.83 324	72.54 91	90.19 113	22.38 420	86.66 285	73.28 119	76.39 144	86.85 236

new-patchmatchnet		48.21 426	46.55 427	53.18 445	57.73 465	18.19 493	70.24 414	71.02 418	45.70 414	33.70 466	60.23 459	18.00 445	69.86 453	27.97 447	34.35 464	71.49 451

pmmvs6		59.64 361	57.15 368	67.09 376	66.01 435	36.86 434	80.50 321	78.64 316	45.05 419	49.05 401	73.94 382	27.28 383	86.10 304	43.96 374	49.94 410	78.31 389

pmmvs5		62.80 342	61.18 338	67.66 370	69.53 417	42.37 404	82.65 261	75.19 372	54.30 347	52.03 378	78.51 329	31.64 357	80.67 377	48.60 344	58.15 352	79.95 372

test_post1							70.84 413				14.72 498	34.33 324	83.86 345	48.80 342

test_post											16.22 495	37.52 263	84.72 336

Fast-Effi-MVS+		72.73 154	71.15 166	77.48 117	82.75 140	54.76 97	86.77 106	80.64 264	63.05 170	65.93 177	84.01 245	44.42 168	89.03 174	56.45 282	76.36 147	88.64 182

patchmatchnet-post											59.74 461	38.41 246	79.91 391

Anonymous20231211		66.08 309	63.67 312	73.31 264	83.07 125	48.75 273	86.01 126	84.67 177	45.27 417	56.54 337	76.67 357	28.06 377	88.95 181	52.78 313	59.95 331	82.23 335

pmmvs-eth3d		55.97 393	52.78 397	65.54 392	61.02 459	46.44 344	75.36 373	67.72 435	49.61 383	43.65 429	67.58 433	21.63 426	77.04 417	44.11 373	44.33 439	73.15 441

GG-mvs-BLEND				77.77 109	86.68 51	50.61 213	68.67 423	88.45 58		68.73 150	87.45 188	59.15 12	90.67 108	54.83 294	87.67 18	92.03 48

xiu_mvs_v1_base_debi		71.60 182	70.29 186	75.55 184	77.26 298	53.15 143	85.34 157	79.37 296	55.83 324	72.54 91	90.19 113	22.38 420	86.66 285	73.28 119	76.39 144	86.85 236

Anonymous20231206		59.08 368	57.59 365	63.55 405	68.77 423	32.14 454	80.26 327	79.78 285	50.00 381	49.39 399	72.39 402	26.64 389	78.36 401	33.12 425	57.94 357	80.14 370

MTAPA		72.73 154	71.22 164	77.27 126	81.54 182	53.57 127	67.06 430	81.31 250	59.41 242	68.39 152	90.96 89	36.07 297	89.01 175	73.80 112	82.45 70	89.23 165

MTMP							87.27 88	15.34 503

gm-plane-assit					83.24 119	54.21 115			70.91 30		88.23 162		95.25 15	66.37 172

test9_res														78.72 65	85.44 44	91.39 77

MVP-Stereo		70.97 196	70.44 179	72.59 286	76.03 323	51.36 195	85.02 178	86.99 88	60.31 226	56.53 338	78.92 326	40.11 229	90.00 131	60.00 239	90.01 7	76.41 413
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					85.68 62	55.42 59	87.59 77	84.00 194	57.72 280	72.99 85	90.98 87	44.87 161	88.58 197

train_agg		76.91 56	76.40 63	78.45 89	85.68 62	55.42 59	87.59 77	84.00 194	57.84 278	72.99 85	90.98 87	44.99 157	88.58 197	78.19 69	85.32 45	91.34 82

gg-mvs-nofinetune		67.43 277	64.53 305	76.13 163	85.95 58	47.79 316	64.38 437	88.28 61	39.34 440	66.62 167	41.27 480	58.69 16	89.00 176	49.64 336	86.62 32	91.59 69

SCA		63.84 329	60.01 351	75.32 195	78.58 271	57.92 13	61.61 449	77.53 340	56.71 306	57.75 316	70.77 419	31.97 350	79.91 391	48.80 342	56.36 369	88.13 202

Patchmatch-test		53.33 407	48.17 420	68.81 358	73.31 364	42.38 403	42.98 477	58.23 457	32.53 462	38.79 452	70.77 419	39.66 234	73.51 440	25.18 455	52.06 405	90.55 117

test_8					85.72 61	55.31 64	87.60 76	83.88 197	57.84 278	72.84 89	90.99 86	44.99 157	88.34 212

MS-PatchMatch		72.34 163	71.26 163	75.61 180	82.38 149	55.55 55	88.00 61	89.95 23	65.38 120	56.51 339	80.74 305	32.28 346	92.89 40	57.95 262	88.10 16	78.39 388

Patchmatch-RL test		58.72 374	54.32 387	71.92 312	63.91 449	44.25 378	61.73 448	55.19 462	57.38 291	49.31 400	54.24 471	37.60 261	80.89 372	62.19 216	47.28 428	90.63 114

cdsmvs_eth3d_5k		18.33 462	24.44 454	0.00 485	0.00 507	0.00 509	0.00 496	89.40 28	0.00 501	0.00 504	92.02 63	38.55 245	0.00 502	0.00 502	0.00 500	0.00 500

pcd_1.5k_mvsjas		3.15 469	4.20 472	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	37.77 253	0.00 502	0.00 502	0.00 500	0.00 500

agg_prior2														75.65 88	85.11 52	91.01 101

agg_prior					85.64 65	54.92 89		83.61 205		72.53 94			88.10 223

tmp_tt		9.44 464	10.68 467	5.73 482	2.49 505	4.21 506	10.48 495	18.04 501	0.34 499	12.59 491	20.49 493	11.39 465	7.03 501	13.84 484	6.46 498	5.95 496

canonicalmvs		78.17 36	77.86 36	79.12 56	84.30 94	54.22 113	87.71 68	84.57 179	67.70 74	77.70 48	92.11 61	50.90 63	89.95 134	78.18 71	77.54 126	93.20 16

anonymousdsp		60.46 358	57.65 364	68.88 355	63.63 451	45.09 367	72.93 393	78.63 317	46.52 405	51.12 386	72.80 397	21.46 427	83.07 357	57.79 266	53.97 392	78.47 385

alignmvs		78.08 38	77.98 33	78.39 92	83.53 110	53.22 141	89.77 32	85.45 128	66.11 105	76.59 55	91.99 65	54.07 44	89.05 173	77.34 77	77.00 134	92.89 24

nrg030		72.27 168	71.56 157	74.42 225	75.93 327	50.60 214	86.97 95	83.21 212	62.75 178	67.15 163	84.38 239	50.07 72	86.66 285	71.19 136	62.37 316	85.99 256

v144192		67.86 265	65.76 283	74.16 235	71.68 386	53.09 147	84.14 212	80.83 261	62.85 177	59.21 284	77.28 345	39.30 238	88.00 227	58.67 249	57.88 360	81.40 350

FIs		70.00 218	70.24 189	69.30 352	77.93 284	38.55 427	83.99 217	87.72 73	66.86 90	57.66 317	84.17 243	52.28 52	85.31 324	52.72 316	68.80 249	84.02 293

v1921920		67.45 276	65.23 297	74.10 238	71.51 389	52.90 153	83.75 226	80.44 269	62.48 186	59.12 285	77.13 346	36.98 277	87.90 230	57.53 269	58.14 354	81.49 345

UA-Net		67.32 283	66.23 271	70.59 334	78.85 262	41.23 414	73.60 387	75.45 370	61.54 202	66.61 168	84.53 238	38.73 244	86.57 290	42.48 382	74.24 184	83.98 297

v1192		67.96 264	65.74 284	74.63 220	71.79 384	53.43 134	84.06 215	80.99 259	63.19 167	59.56 275	77.46 341	37.50 265	88.65 193	58.20 257	58.93 343	81.79 340

FC-MVSNet-test		67.49 275	67.91 228	66.21 386	76.06 321	33.06 448	80.82 316	87.18 84	64.44 132	54.81 352	82.87 264	50.40 71	82.60 359	48.05 349	66.55 268	82.98 327

v1144		68.81 246	66.82 257	74.80 216	72.34 379	53.46 129	84.68 193	81.77 242	64.25 137	60.28 265	77.91 334	40.23 226	88.95 181	60.37 236	59.52 336	81.97 337

sosnet-low-res		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

HFP-MVS		74.37 121	73.13 130	78.10 100	84.30 94	53.68 125	85.58 148	84.36 183	56.82 303	65.78 180	90.56 99	40.70 222	90.90 102	69.18 152	80.88 81	89.71 148

v148		68.24 260	66.35 267	73.88 245	71.76 385	51.47 193	84.23 208	81.90 239	63.69 155	58.94 288	76.44 359	43.72 177	87.78 242	60.63 229	55.86 379	82.39 334

sosnet		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

uncertanet		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

AllTest		47.32 428	44.66 430	55.32 443	65.08 443	37.50 432	62.96 444	54.25 465	35.45 458	33.42 468	72.82 395	9.98 469	59.33 467	24.13 458	43.84 441	69.13 454

TestCases				55.32 443	65.08 443	37.50 432		54.25 465	35.45 458	33.42 468	72.82 395	9.98 469	59.33 467	24.13 458	43.84 441	69.13 454

v7n		62.50 345	59.27 356	72.20 299	67.25 433	49.83 240	77.87 356	80.12 276	52.50 361	48.80 403	73.07 392	32.10 348	87.90 230	46.83 357	54.92 385	78.86 379

region2R		73.75 134	72.55 136	77.33 122	83.90 104	52.98 151	85.54 152	84.09 192	56.83 302	65.10 190	90.45 103	37.34 268	90.24 126	68.89 154	80.83 83	88.77 179

RRT-MVS		73.29 143	71.37 162	79.07 58	84.63 84	54.16 118	78.16 353	86.64 99	61.67 199	60.17 266	82.35 283	40.63 223	92.26 60	70.19 143	77.87 122	90.81 109

balanced_ft_v1		75.25 104	73.90 117	79.29 49	85.59 66	56.72 34	74.35 382	87.27 80	60.24 227	59.07 286	85.17 224	47.76 94	90.51 115	82.62 35	83.06 64	90.64 113

PS-MVSNAJss		68.78 248	67.17 252	73.62 256	73.01 370	48.33 290	84.95 182	84.81 165	59.30 247	58.91 291	79.84 314	37.77 253	88.86 186	62.83 210	63.12 309	83.67 311

PS-MVSNAJ		80.06 17	79.52 18	81.68 15	85.58 67	60.97 3	91.69 12	87.02 87	70.62 32	80.75 28	93.22 33	37.77 253	92.50 52	82.75 33	86.25 36	91.57 71

jajsoiax		63.21 337	60.84 341	70.32 339	68.33 427	44.45 374	81.23 307	81.05 254	53.37 355	50.96 389	77.81 337	17.49 449	85.49 322	59.31 242	58.05 355	81.02 359

mvs_tets		62.96 340	60.55 343	70.19 340	68.22 430	44.24 379	80.90 314	80.74 262	52.99 358	50.82 393	77.56 338	16.74 453	85.44 323	59.04 245	57.94 357	80.89 360

EI-MVSNet-UG-set		72.37 162	71.73 154	74.29 232	81.60 178	49.29 258	81.85 284	88.64 48	65.29 124	65.05 191	88.29 160	43.18 186	91.83 69	63.74 202	67.97 256	81.75 341

EI-MVSNet-Vis-set		73.19 145	72.60 135	74.99 211	82.56 146	49.80 241	82.55 266	89.00 35	66.17 103	65.89 178	88.98 137	43.83 172	92.29 58	65.38 188	69.01 244	82.87 329

HPM-MVS++		80.50 14	80.71 14	79.88 44	87.34 46	55.20 71	89.93 29	87.55 77	66.04 110	79.46 38	93.00 40	53.10 48	91.76 70	80.40 51	89.56 9	92.68 30

test_prior4						56.39 42	87.15 92

XVS		72.92 148	71.62 156	76.81 144	83.41 112	52.48 160	84.88 184	83.20 213	58.03 271	63.91 216	89.63 126	35.50 306	89.78 140	65.50 180	80.50 88	88.16 199

v1240		66.99 292	64.68 303	73.93 243	71.38 393	52.66 158	83.39 240	79.98 279	61.97 194	58.44 307	77.11 347	35.25 308	87.81 235	56.46 281	58.15 352	81.33 353

pm-mvs1		64.12 326	62.56 320	68.78 359	71.68 386	38.87 425	82.89 256	81.57 245	55.54 329	53.89 364	77.82 336	37.73 256	86.74 282	48.46 347	53.49 398	80.72 362

test_prior2							89.04 48		61.88 196	73.55 76	91.46 81	48.01 91		74.73 97	85.46 43

X-MVStestdata		65.85 311	62.20 325	76.81 144	83.41 112	52.48 160	84.88 184	83.20 213	58.03 271	63.91 216	4.82 499	35.50 306	89.78 140	65.50 180	80.50 88	88.16 199

test_prior				78.39 92	86.35 56	54.91 92		85.45 128					89.70 148			90.55 117

旧先验2							81.73 290		45.53 416	74.66 64			70.48 452	58.31 255

新几何2							81.61 296

新几何1				73.30 265	83.10 122	53.48 128		71.43 413	45.55 415	66.14 173	87.17 194	33.88 329	80.54 381	48.50 345	80.33 92	85.88 261

旧先验1					81.57 181	47.48 322		71.83 407			88.66 144	36.94 278			78.34 117	88.67 181

无先验							85.19 166	78.00 330	49.08 385				85.13 330	52.78 313		87.45 219

原ACMM2							83.77 225

原ACMM1				76.13 163	84.89 81	54.59 107		85.26 139	51.98 364	66.70 165	87.07 196	40.15 228	89.70 148	51.23 327	85.06 53	84.10 291

test222					79.36 246	50.97 201	77.99 355	67.84 434	42.54 434	62.84 236	86.53 204	30.26 366			76.91 135	85.23 270

testdata2													77.81 412	45.64 364

segment_acmp												44.97 159

testdata				67.08 377	77.59 289	45.46 365		69.20 429	44.47 423	71.50 115	88.34 158	31.21 360	70.76 451	52.20 322	75.88 157	85.03 274

testdata1							77.55 358		64.14 141

v8		67.25 284	64.99 301	74.04 239	72.89 373	53.31 139	82.37 273	80.11 277	61.54 202	54.29 360	76.02 368	42.89 192	88.41 208	58.43 251	56.36 369	80.39 367

1314		71.11 192	69.41 201	76.22 158	79.32 248	50.49 217	80.23 328	85.14 151	59.44 241	58.93 289	88.89 140	33.83 330	89.60 151	61.49 222	77.42 129	88.57 187

LFMVS		78.52 28	77.14 48	82.67 4	89.58 14	58.90 8	91.27 19	88.05 65	63.22 166	74.63 65	90.83 96	41.38 212	94.40 21	75.42 92	79.90 99	94.72 2

VDD-MVS		76.08 80	74.97 95	79.44 46	84.27 97	53.33 138	91.13 20	85.88 115	65.33 122	72.37 96	89.34 131	32.52 343	92.76 46	77.90 74	75.96 156	92.22 41

VDDNet		74.37 121	72.13 148	81.09 21	79.58 240	56.52 39	90.02 26	86.70 96	52.61 360	71.23 118	87.20 193	31.75 356	93.96 27	74.30 105	75.77 163	92.79 28

v10		66.61 299	64.20 310	73.83 248	72.59 376	53.37 135	81.88 283	79.91 283	61.11 210	54.09 362	75.60 370	40.06 230	88.26 219	56.47 280	56.10 375	79.86 373

VPNet		72.07 170	71.42 161	74.04 239	78.64 270	47.17 330	89.91 31	87.97 66	72.56 12	64.66 200	85.04 230	41.83 207	88.33 213	61.17 225	60.97 324	86.62 243

MVS		76.91 56	75.48 81	81.23 20	84.56 86	55.21 68	80.23 328	91.64 4	58.65 263	65.37 186	91.48 80	45.72 142	95.05 17	72.11 134	89.52 10	93.44 10

v2v482		69.55 231	67.64 239	75.26 203	72.32 380	53.83 121	84.93 183	81.94 235	65.37 121	60.80 260	79.25 322	41.62 208	88.98 179	63.03 207	59.51 337	82.98 327

V42		67.66 270	65.60 288	73.86 246	70.69 402	53.63 126	81.50 302	78.61 318	63.85 149	59.49 278	77.49 340	37.98 250	87.65 248	62.33 213	58.43 347	80.29 368

SD-MVS		76.18 76	74.85 98	80.18 35	85.39 71	56.90 29	85.75 137	82.45 226	56.79 305	74.48 68	91.81 69	43.72 177	90.75 106	74.61 98	78.65 112	92.91 23
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
GA-MVS		69.04 240	66.70 261	76.06 165	75.11 341	52.36 164	83.12 250	80.23 273	63.32 164	60.65 262	79.22 323	30.98 362	88.37 209	61.25 223	66.41 270	87.46 218

MSLP-MVS++		74.21 123	72.25 144	80.11 41	81.45 186	56.47 40	86.32 115	79.65 290	58.19 269	66.36 172	92.29 57	36.11 295	90.66 109	67.39 165	82.49 69	93.18 18

APDe-MVS		78.44 30	78.20 30	79.19 51	88.56 28	54.55 108	89.76 33	87.77 71	55.91 323	78.56 43	92.49 53	48.20 86	92.65 48	79.49 56	83.04 65	90.39 122
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		69.62 230	68.23 224	73.80 249	81.58 180	48.22 294	81.91 282	79.50 293	48.21 393	64.24 211	89.75 124	31.91 353	87.55 253	63.08 205	73.85 189	85.64 265

ADS-MVSNet2		55.21 397	51.44 402	66.51 384	80.60 211	49.56 246	55.03 464	65.44 440	44.72 421	51.00 387	61.19 456	22.83 416	75.41 431	28.54 443	53.63 395	74.57 429

EI-MVSNet		69.70 228	68.70 214	72.68 283	75.00 344	48.90 268	79.54 340	87.16 85	61.05 212	63.88 218	83.74 250	45.87 138	90.44 118	57.42 271	64.68 289	78.70 381

Regformer		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

CVMVSNet		60.85 356	60.44 345	62.07 415	75.00 344	32.73 450	79.54 340	73.49 393	36.98 450	56.28 341	83.74 250	29.28 372	69.53 454	46.48 359	63.23 305	83.94 300

pmmvs4		63.34 336	61.07 340	70.16 341	70.14 410	50.53 216	79.97 335	71.41 414	55.08 336	54.12 361	78.58 328	32.79 341	82.09 365	50.33 331	57.22 365	77.86 395

EU-MVSNet		52.63 409	50.72 405	58.37 434	62.69 456	28.13 473	72.60 396	75.97 364	30.94 467	40.76 446	72.11 412	20.16 434	70.80 450	35.11 415	46.11 435	76.19 415

VNet		77.99 40	77.92 35	78.19 98	87.43 45	50.12 232	90.93 22	91.41 8	67.48 77	75.12 60	90.15 116	46.77 113	91.00 96	73.52 115	78.46 115	93.44 10

test-LLR		69.65 229	69.01 212	71.60 317	78.67 266	48.17 296	85.13 169	79.72 286	59.18 251	63.13 232	82.58 274	36.91 279	80.24 385	60.56 231	75.17 172	86.39 250

TESTMET0.1,1		72.86 150	72.33 141	74.46 223	81.98 159	50.77 209	85.13 169	85.47 126	66.09 106	67.30 161	83.69 253	37.27 269	83.57 351	65.06 191	78.97 111	89.05 171

test-mter		68.36 255	67.29 248	71.60 317	78.67 266	48.17 296	85.13 169	79.72 286	53.38 354	63.13 232	82.58 274	27.23 384	80.24 385	60.56 231	75.17 172	86.39 250

VPA-MVSNet		71.12 191	70.66 175	72.49 289	78.75 264	44.43 375	87.64 71	90.02 21	63.97 146	65.02 192	81.58 298	42.14 200	87.42 258	63.42 204	63.38 303	85.63 266

ACMMPR		73.76 133	72.61 134	77.24 129	83.92 103	52.96 152	85.58 148	84.29 184	56.82 303	65.12 189	90.45 103	37.24 271	90.18 128	69.18 152	80.84 82	88.58 186

testgi		54.25 400	52.57 399	59.29 431	62.76 455	21.65 485	72.21 403	70.47 420	53.25 356	41.94 437	77.33 344	14.28 459	77.95 409	29.18 439	51.72 406	78.28 390

test20.03		55.22 396	54.07 389	58.68 433	63.14 454	25.00 476	77.69 357	74.78 375	52.64 359	43.43 430	72.39 402	26.21 391	74.76 433	29.31 438	47.05 431	76.28 414

thres600view7		66.46 302	65.12 299	70.47 335	83.41 112	43.80 384	82.15 275	87.78 69	59.37 243	56.02 342	82.21 285	43.73 175	86.90 275	26.51 452	64.94 283	80.71 363

ADS-MVSNet		56.17 391	51.95 401	68.84 356	80.60 211	53.07 148	55.03 464	70.02 424	44.72 421	51.00 387	61.19 456	22.83 416	78.88 397	28.54 443	53.63 395	74.57 429

MP-MVS		74.99 111	74.33 109	76.95 139	82.89 135	53.05 149	85.63 147	83.50 206	57.86 277	67.25 162	90.24 110	43.38 185	88.85 189	76.03 84	82.23 71	88.96 172
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		6.14 467	8.18 470	0.01 483	0.01 506	0.00 509	73.40 391	0.00 507	0.00 501	0.02 502	0.15 501	0.00 505	0.00 502	0.02 500	0.00 500	0.02 498

thres400		67.40 281	66.13 273	71.19 325	84.05 100	45.07 368	83.40 238	87.71 74	60.79 219	57.79 314	82.76 267	43.53 180	87.80 238	28.80 440	66.36 272	80.71 363

test123		6.01 468	8.01 471	0.01 483	0.00 507	0.01 508	71.93 408	0.00 507	0.00 501	0.02 502	0.11 502	0.00 505	0.00 502	0.02 500	0.00 500	0.02 498

thres200		68.71 249	67.27 250	73.02 269	84.73 82	46.76 336	85.03 176	87.73 72	62.34 188	59.87 268	83.45 257	43.15 187	88.32 214	31.25 432	67.91 257	83.98 297

test0.0.03 1		62.54 343	62.44 321	62.86 413	72.28 382	29.51 467	82.93 255	78.78 312	59.18 251	53.07 370	82.41 278	36.91 279	77.39 415	37.45 395	58.96 342	81.66 343

pmmvs3		45.53 432	41.55 437	57.44 436	48.97 482	39.68 420	70.06 415	57.66 458	28.32 471	34.06 465	57.29 466	8.50 475	66.85 457	34.86 417	34.26 465	65.80 463

EMVS		18.42 461	17.66 465	20.71 479	34.13 493	12.64 499	46.94 471	29.94 492	10.46 493	5.58 499	14.93 497	4.23 488	38.83 490	5.24 498	7.51 496	10.67 495

E-PMN		19.16 460	18.40 464	21.44 478	36.19 491	13.63 498	47.59 470	30.89 490	10.73 491	5.91 498	16.59 494	3.66 489	39.77 489	5.95 496	8.14 494	10.92 494

PGM-MVS		72.60 156	71.20 165	76.80 146	82.95 131	52.82 156	83.07 252	82.14 228	56.51 315	63.18 231	89.81 123	35.68 303	89.76 142	67.30 166	80.19 93	87.83 208

LCM-MVSNet-Re		58.82 372	56.54 371	65.68 390	79.31 249	29.09 470	61.39 451	45.79 471	60.73 221	37.65 455	72.47 400	31.42 358	81.08 371	49.66 335	70.41 234	86.87 233

LCM-MVSNet		28.07 449	23.85 457	40.71 461	27.46 501	18.93 488	30.82 489	46.19 470	12.76 488	16.40 486	34.70 487	1.90 496	48.69 483	20.25 470	24.22 480	54.51 475

MCST-MVS		83.01 1	83.30 2	82.15 11	92.84 2	57.58 17	93.77 1	91.10 13	75.95 3	77.10 51	93.09 36	54.15 43	95.57 13	85.80 13	85.87 39	93.31 12

mvs_anonymous		72.29 166	70.74 172	76.94 140	82.85 137	54.72 101	78.43 352	81.54 246	63.77 151	61.69 251	79.32 321	51.11 60	85.31 324	62.15 217	75.79 158	90.79 110

MVS_Test		75.85 88	74.93 96	78.62 74	84.08 99	55.20 71	83.99 217	85.17 143	68.07 66	73.38 79	82.76 267	50.44 70	89.00 176	65.90 178	80.61 86	91.64 67

MDA-MVSNet-bldmvs		51.56 416	47.75 424	63.00 410	71.60 388	47.32 327	69.70 419	72.12 404	43.81 428	27.65 480	63.38 447	21.97 425	75.96 427	27.30 450	32.19 468	65.70 464

CDPH-MVS		76.05 81	75.19 87	78.62 74	86.51 53	54.98 81	87.32 84	84.59 178	58.62 264	70.75 130	90.85 95	43.10 190	90.63 112	70.50 141	84.51 58	90.24 128

test12				79.24 50	86.89 49	56.08 47		85.16 145		72.27 98		47.15 104	91.10 91		85.93 38	90.54 119

casdiffmvs		77.36 49	76.85 54	78.88 62	80.40 224	54.66 106	87.06 93	85.88 115	72.11 16	71.57 109	88.63 148	50.89 66	90.35 121	76.00 85	79.11 108	91.63 68
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
diffmvs		75.11 109	74.65 105	76.46 153	78.52 272	53.35 136	83.28 243	79.94 281	70.51 35	71.64 108	88.72 142	46.02 130	86.08 307	77.52 75	75.75 164	89.96 144
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline2		75.15 108	74.54 107	76.98 138	81.67 172	51.74 186	83.84 223	91.94 3	69.97 44	58.98 287	86.02 212	59.73 10	91.73 72	68.37 159	70.40 235	87.48 217

baseline1		72.51 159	72.12 149	73.69 253	85.05 77	44.46 373	83.51 232	86.13 111	71.61 21	64.64 201	87.97 173	55.00 38	89.48 156	59.07 244	56.05 376	87.13 228

YYNet1		53.82 403	49.96 409	65.41 394	70.09 412	48.95 265	72.30 401	71.66 411	44.25 426	31.89 472	63.07 449	23.73 412	73.95 436	33.26 423	39.40 453	73.34 437

PMMVS2		26.71 453	22.98 458	37.87 466	36.89 490	8.51 504	42.51 478	29.32 493	19.09 481	13.01 490	37.54 481	2.23 494	53.11 477	14.54 482	11.71 492	51.99 478

MDA-MVSNet_test_wron		53.82 403	49.95 410	65.43 393	70.13 411	49.05 261	72.30 401	71.65 412	44.23 427	31.85 473	63.13 448	23.68 413	74.01 435	33.25 424	39.35 454	73.23 440

tpmvs		62.45 347	59.42 354	71.53 320	83.93 102	54.32 111	70.03 416	77.61 339	51.91 365	53.48 368	68.29 430	37.91 251	86.66 285	33.36 422	58.27 350	73.62 435

PM-MVS		46.92 429	43.76 435	56.41 440	52.18 473	32.26 453	63.21 443	38.18 482	37.99 446	40.78 445	66.20 438	5.09 486	65.42 458	48.19 348	41.99 445	71.54 450

HQP_MVS		70.96 197	69.91 195	74.12 237	77.95 282	49.57 243	85.76 135	82.59 222	63.60 157	62.15 245	83.28 261	36.04 298	88.30 216	65.46 183	72.34 207	84.49 282

plane_prior7					77.95 282	48.46 284

plane_prior6					78.42 275	49.39 256						36.04 298

plane_prior5								82.59 222					88.30 216	65.46 183	72.34 207	84.49 282

plane_prior4											83.28 261

plane_prior3						48.95 265			64.01 145	62.15 245

plane_prior2							85.76 135		63.60 157

plane_prior1					78.31 278

plane_prior						49.57 243	87.43 80		64.57 131						72.84 200

PS-CasMVS		58.12 380	57.03 370	61.37 423	68.24 429	33.80 446	76.73 363	78.01 329	51.20 372	47.54 412	76.20 366	32.85 339	72.76 444	35.17 414	47.37 427	77.55 401

UniMVSNet_NR-MVSNet		68.82 245	68.29 222	70.40 338	75.71 330	42.59 399	84.23 208	86.78 93	66.31 99	58.51 301	82.45 277	51.57 57	84.64 338	53.11 307	55.96 377	83.96 299

PEN-MVS		58.35 379	57.15 368	61.94 418	67.55 432	34.39 439	77.01 359	78.35 325	51.87 366	47.72 409	76.73 356	33.91 327	73.75 438	34.03 419	47.17 429	77.68 398

TransMVSNet (Re)		62.82 341	60.76 342	69.02 354	73.98 360	41.61 409	86.36 113	79.30 303	56.90 298	52.53 372	76.44 359	41.85 206	87.60 252	38.83 392	40.61 448	77.86 395

DTE-MVSNet		57.03 385	55.73 380	60.95 427	65.94 436	32.57 451	75.71 366	77.09 349	51.16 373	46.65 419	76.34 361	32.84 340	73.22 442	30.94 433	44.87 438	77.06 403

DU-MVS		66.84 296	65.74 284	70.16 341	73.27 367	42.59 399	81.50 302	82.92 219	63.53 159	58.51 301	82.11 287	40.75 219	84.64 338	53.11 307	55.96 377	83.24 319

UniMVSNet (Re)		67.71 269	66.80 258	70.45 336	74.44 351	42.93 395	82.42 272	84.90 162	63.69 155	59.63 273	80.99 301	47.18 103	85.23 327	51.17 328	56.75 368	83.19 321

CP-MVSNet		58.54 378	57.57 366	61.46 422	68.50 425	33.96 444	76.90 361	78.60 319	51.67 369	47.83 408	76.60 358	34.99 314	72.79 443	35.45 409	47.58 425	77.64 400

WR-MVS_H		58.91 371	58.04 363	61.54 421	69.07 421	33.83 445	76.91 360	81.99 234	51.40 370	48.17 404	74.67 375	40.23 226	74.15 434	31.78 429	48.10 421	76.64 410

WR-MVS		67.58 272	66.76 259	70.04 345	75.92 328	45.06 371	86.23 117	85.28 138	64.31 135	58.50 303	81.00 300	44.80 165	82.00 366	49.21 340	55.57 382	83.06 324

NR-MVSNet		67.25 284	65.99 277	71.04 328	73.27 367	43.91 382	85.32 161	84.75 169	66.05 109	53.65 367	82.11 287	45.05 155	85.97 314	47.55 351	56.18 374	83.24 319

Baseline_NR-MVSNet		65.49 316	64.27 309	69.13 353	74.37 354	41.65 408	83.39 240	78.85 309	59.56 238	59.62 274	76.88 354	40.75 219	87.44 257	49.99 332	55.05 384	78.28 390

TranMVSNet+NR-MVSNet		66.94 294	65.61 287	70.93 330	73.45 363	43.38 389	83.02 254	84.25 186	65.31 123	58.33 308	81.90 291	39.92 233	85.52 320	49.43 337	54.89 386	83.89 302

TSAR-MVS + GP.		77.82 41	77.59 40	78.49 85	85.25 75	50.27 231	90.02 26	90.57 18	56.58 313	74.26 70	91.60 77	54.26 41	92.16 62	75.87 86	79.91 98	93.05 21

n2								0.00 507

nn								0.00 507

mPP-MVS		71.79 179	70.38 183	76.04 166	82.65 144	52.06 172	84.45 201	81.78 241	55.59 327	62.05 248	89.68 125	33.48 332	88.28 218	65.45 185	78.24 118	87.77 210

door-mid								41.31 479

XVG-OURS-SEG-HR		62.02 349	59.54 353	69.46 350	65.30 440	45.88 358	65.06 434	73.57 391	46.45 406	57.42 325	83.35 260	26.95 386	78.09 404	53.77 302	64.03 293	84.42 284

mvsmamba		69.38 233	67.52 244	74.95 212	82.86 136	52.22 171	67.36 428	76.75 354	61.14 209	49.43 398	82.04 289	37.26 270	84.14 342	73.93 109	76.91 135	88.50 193

MVSFormer		73.53 139	72.19 146	77.57 114	83.02 128	55.24 66	81.63 294	81.44 248	50.28 377	76.67 53	90.91 93	44.82 163	86.11 302	60.83 227	80.09 94	91.36 79

jason		77.01 55	76.45 62	78.69 69	79.69 238	54.74 98	90.56 24	83.99 196	68.26 60	74.10 71	90.91 93	42.14 200	89.99 132	79.30 58	79.12 107	91.36 79
jason: jason.
lupinMVS		78.38 32	78.11 32	79.19 51	83.02 128	55.24 66	91.57 15	84.82 164	69.12 54	76.67 53	92.02 63	44.82 163	90.23 127	80.83 50	80.09 94	92.08 44

test_djsdf		63.84 329	61.56 332	70.70 333	68.78 422	44.69 372	81.63 294	81.44 248	50.28 377	52.27 375	76.26 362	26.72 388	86.11 302	60.83 227	55.84 380	81.29 356

HPM-MVS_fast		67.86 265	66.28 270	72.61 285	80.67 210	48.34 288	81.18 308	75.95 365	50.81 374	59.55 276	88.05 170	27.86 379	85.98 312	58.83 246	73.58 191	83.51 314

K. test v3		54.04 401	49.42 414	67.92 369	68.55 424	42.57 402	75.51 371	63.07 450	52.07 363	39.21 449	64.59 445	19.34 437	82.21 362	37.11 398	25.31 478	78.97 378

lessismore_v0				67.98 368	64.76 446	41.25 413		45.75 472		36.03 460	65.63 442	19.29 439	84.11 343	35.67 407	21.24 484	78.59 384

SixPastTwentyTwo		54.37 398	50.10 407	67.21 375	70.70 401	41.46 412	74.73 376	64.69 442	47.56 398	39.12 450	69.49 424	18.49 444	84.69 337	31.87 428	34.20 466	75.48 418

OurMVSNet-221017-0		52.39 412	48.73 416	63.35 409	65.21 441	38.42 428	68.54 424	64.95 441	38.19 444	39.57 448	71.43 415	13.23 461	79.92 389	37.16 396	40.32 450	71.72 448

HPM-MVS		72.60 156	71.50 158	75.89 171	82.02 158	51.42 194	80.70 319	83.05 215	56.12 322	64.03 214	89.53 127	37.55 262	88.37 209	70.48 142	80.04 96	87.88 207
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		61.88 350	59.34 355	69.49 349	65.37 439	46.27 350	64.80 435	73.49 393	47.04 402	57.41 326	82.85 265	25.15 401	78.18 402	53.00 310	64.98 281	84.01 294

XVG-ACMP-BASELINE		56.03 392	52.85 396	65.58 391	61.91 457	40.95 416	63.36 440	72.43 402	45.20 418	46.02 421	74.09 379	9.20 472	78.12 403	45.13 365	58.27 350	77.66 399

casdiffmvs_mvg		77.75 43	77.28 45	79.16 53	80.42 223	54.44 110	87.76 67	85.46 127	71.67 20	71.38 116	88.35 157	51.58 56	91.22 86	79.02 60	79.89 100	91.83 58
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test		66.44 303	64.58 304	72.02 304	74.42 352	48.60 277	83.07 252	80.64 264	54.69 342	53.75 365	83.83 248	25.73 396	86.98 270	60.33 237	64.71 286	80.48 365

LGP-MVS_train				72.02 304	74.42 352	48.60 277		80.64 264	54.69 342	53.75 365	83.83 248	25.73 396	86.98 270	60.33 237	64.71 286	80.48 365

baseline		76.86 59	76.24 66	78.71 68	80.47 218	54.20 117	83.90 221	84.88 163	71.38 25	71.51 112	89.15 136	50.51 69	90.55 114	75.71 87	78.65 112	91.39 77

test11								84.25 186

door								43.27 475

EPNet_dtu		66.25 306	66.71 260	64.87 398	78.66 269	34.12 443	82.80 258	75.51 368	61.75 197	64.47 209	86.90 197	37.06 276	72.46 445	43.65 375	69.63 242	88.02 205
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		76.24 75	74.03 115	82.88 2	83.09 124	62.84 2	85.73 141	85.39 130	69.79 47	64.87 198	83.49 256	41.52 211	93.69 34	70.55 139	81.82 75	92.12 43

EPNet		78.36 33	78.49 28	77.97 102	85.49 69	52.04 173	89.36 41	84.07 193	73.22 8	77.03 52	91.72 72	49.32 81	90.17 129	73.46 117	82.77 66	91.69 65
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						51.56 190

HQP-NCC					79.02 257		88.00 61		65.45 116	64.48 206

ACMP_Plane					79.02 257		88.00 61		65.45 116	64.48 206

APD-MVS		76.15 78	75.68 74	77.54 116	88.52 29	53.44 132	87.26 89	85.03 155	53.79 350	74.91 63	91.68 74	43.80 173	90.31 123	74.36 103	81.82 75	88.87 175
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														66.70 169

HQP4-MVS										64.47 209			88.61 195			84.91 278

HQP3-MVS								83.68 201							73.12 196

HQP2-MVS												37.35 266

CNVR-MVS		81.76 9	81.90 8	81.33 19	90.04 11	57.70 15	91.71 11	88.87 40	70.31 36	77.64 50	93.87 13	52.58 51	93.91 28	84.17 22	87.92 17	92.39 34

NCCC		79.57 20	79.23 21	80.59 25	89.50 16	56.99 27	91.38 16	88.17 62	67.71 73	73.81 74	92.75 47	46.88 108	93.28 35	78.79 64	84.07 60	91.50 75

114514_t		69.87 222	67.88 232	75.85 172	88.38 31	52.35 165	86.94 97	83.68 201	53.70 351	55.68 345	85.60 217	30.07 368	91.20 87	55.84 286	71.02 224	83.99 295

CP-MVS		72.59 158	71.46 159	76.00 168	82.93 133	52.32 166	86.93 99	82.48 225	55.15 335	63.65 226	90.44 106	35.03 313	88.53 203	68.69 157	77.83 124	87.15 227

DSMNet-mixed		38.35 439	35.36 444	47.33 454	48.11 484	14.91 497	37.87 483	36.60 485	19.18 480	34.37 464	59.56 462	15.53 457	53.01 478	20.14 472	46.89 432	74.07 431

tpm2		70.82 199	68.44 219	77.98 101	80.78 206	56.11 46	74.21 383	81.28 252	60.24 227	68.04 157	75.27 372	52.26 53	88.50 204	55.82 287	68.03 255	89.33 162

NP-MVS					78.76 263	50.43 220					85.12 226

EG-PatchMatch MVS		62.40 348	59.59 352	70.81 331	73.29 365	49.05 261	85.81 133	84.78 167	51.85 367	44.19 426	73.48 390	15.52 458	89.85 138	40.16 388	67.24 261	73.54 436

tpm cat1		66.28 305	62.78 317	76.77 149	81.40 187	57.14 25	70.03 416	77.19 346	53.00 357	58.76 295	70.73 421	46.17 123	86.73 283	43.27 376	64.46 290	86.44 248

SteuartSystems-ACMMP		77.08 54	76.33 64	79.34 48	80.98 197	55.31 64	89.76 33	86.91 89	62.94 172	71.65 107	91.56 78	42.33 196	92.56 51	77.14 79	83.69 62	90.15 134
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		73.89 131	72.30 143	78.66 71	82.36 150	56.58 35	75.56 369	85.30 136	66.06 108	70.50 137	76.88 354	57.02 25	89.06 172	68.27 161	68.74 250	90.33 125

CR-MVSNet		62.47 346	59.04 358	72.77 279	73.97 361	56.57 36	60.52 452	71.72 409	60.04 229	57.49 322	65.86 439	38.94 241	80.31 384	42.86 379	59.93 332	81.42 348

JIA-IIPM		52.33 413	47.77 423	66.03 387	71.20 394	46.92 331	40.00 482	76.48 361	37.10 449	46.73 417	37.02 482	32.96 338	77.88 410	35.97 406	52.45 404	73.29 439

Patchmtry		56.56 388	52.95 395	67.42 373	72.53 377	50.59 215	59.05 456	71.72 409	37.86 447	46.92 416	65.86 439	38.94 241	80.06 388	36.94 401	46.72 433	71.60 449

PatchT		56.60 387	52.97 394	67.48 372	72.94 372	46.16 355	57.30 460	73.78 388	38.77 442	54.37 358	57.26 467	37.52 263	78.06 405	32.02 427	52.79 402	78.23 392

tpmrst		71.04 195	69.77 196	74.86 214	83.19 121	55.86 53	75.64 367	78.73 315	67.88 69	64.99 194	73.73 384	49.96 76	79.56 395	65.92 177	67.85 258	89.14 169

BH-w/o		70.02 217	68.51 218	74.56 221	82.77 139	50.39 222	86.60 111	78.14 328	59.77 234	59.65 272	85.57 218	39.27 239	87.30 262	49.86 334	74.94 179	85.99 256

tpm		68.36 255	67.48 245	70.97 329	79.93 232	51.34 196	76.58 364	78.75 314	67.73 72	63.54 230	74.86 374	48.33 85	72.36 446	53.93 301	63.71 296	89.21 166

DELS-MVS		82.32 5	82.50 5	81.79 13	86.80 50	56.89 30	92.77 2	86.30 106	77.83 1	77.88 47	92.13 58	60.24 8	94.78 20	78.97 61	89.61 8	93.69 9
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
BH-untuned		68.28 258	66.40 266	73.91 244	81.62 176	50.01 235	85.56 150	77.39 343	57.63 283	57.47 324	83.69 253	36.36 289	87.08 268	44.81 367	73.08 199	84.65 281

RPMNet		59.29 363	54.25 388	74.42 225	73.97 361	56.57 36	60.52 452	76.98 350	35.72 456	57.49 322	58.87 464	37.73 256	85.26 326	27.01 451	59.93 332	81.42 348

MVSTER		73.25 144	72.33 141	76.01 167	85.54 68	53.76 124	83.52 228	87.16 85	67.06 85	63.88 218	81.66 295	52.77 49	90.44 118	64.66 194	64.69 288	83.84 303

CPTT-MVS		67.15 287	65.84 281	71.07 327	80.96 199	50.32 228	81.94 281	74.10 382	46.18 413	57.91 311	87.64 186	29.57 369	81.31 369	64.10 196	70.18 237	81.56 344

GBi-Net		67.09 289	65.47 290	71.96 307	82.71 141	46.36 345	83.52 228	83.31 208	58.55 265	57.58 319	76.23 363	36.72 284	86.20 298	47.25 354	63.40 300	83.32 316

PVSNet_Blended_VisFu		73.40 142	72.44 138	76.30 154	81.32 190	54.70 102	85.81 133	78.82 311	63.70 154	64.53 205	85.38 222	47.11 105	87.38 261	67.75 164	77.55 125	86.81 241

PVSNet_BlendedMVS		73.42 141	73.30 124	73.76 250	85.91 59	51.83 181	86.18 119	84.24 188	65.40 119	69.09 147	80.86 303	46.70 114	88.13 221	75.43 90	65.92 278	81.33 353

UnsupCasMVSNet_eth		57.56 383	55.15 382	64.79 399	64.57 447	33.12 447	73.17 392	83.87 198	58.98 257	41.75 439	70.03 423	22.54 419	79.92 389	46.12 363	35.31 460	81.32 355

UnsupCasMVSNet_bld		53.86 402	50.53 406	63.84 402	63.52 453	34.75 437	71.38 410	81.92 237	46.53 404	38.95 451	57.93 465	20.55 431	80.20 387	39.91 389	34.09 467	76.57 411

PVSNet_Blended		76.53 68	76.54 61	76.50 152	85.91 59	51.83 181	88.89 50	84.24 188	67.82 71	69.09 147	89.33 133	46.70 114	88.13 221	75.43 90	81.48 79	89.55 153

FMVSNet5		58.61 375	56.45 372	65.10 397	77.20 301	39.74 419	74.77 375	77.12 348	50.27 379	43.28 432	67.71 432	26.15 393	76.90 421	36.78 403	54.78 387	78.65 383

test1		67.09 289	65.47 290	71.96 307	82.71 141	46.36 345	83.52 228	83.31 208	58.55 265	57.58 319	76.23 363	36.72 284	86.20 298	47.25 354	63.40 300	83.32 316

new_pmnet		33.56 447	31.89 449	38.59 464	49.01 481	20.42 486	51.01 467	37.92 483	20.58 477	23.45 483	46.79 478	6.66 481	49.28 482	20.00 473	31.57 470	46.09 483

FMVSNet3		68.84 244	67.40 246	73.19 268	85.05 77	48.53 280	85.71 143	85.36 131	60.90 218	57.58 319	79.15 324	42.16 199	86.77 281	47.25 354	63.40 300	84.27 288

dp		64.41 322	61.58 331	72.90 273	82.40 148	54.09 119	72.53 397	76.59 360	60.39 225	55.68 345	70.39 422	35.18 310	76.90 421	39.34 390	61.71 319	87.73 211

FMVSNet2		67.57 273	65.79 282	72.90 273	82.71 141	47.97 305	85.15 168	84.93 161	58.55 265	56.71 335	78.26 332	36.72 284	86.67 284	46.15 362	62.94 311	84.07 292

FMVSNet1		64.57 321	62.11 326	71.96 307	77.32 296	46.36 345	83.52 228	83.31 208	52.43 362	54.42 357	76.23 363	27.80 380	86.20 298	42.59 381	61.34 321	83.32 316

N_pmnet		41.25 435	39.77 438	45.66 456	68.50 425	0.82 507	72.51 398	0.38 506	35.61 457	35.26 462	61.51 455	20.07 435	67.74 455	23.51 460	40.63 447	68.42 457

cascas		69.01 241	66.13 273	77.66 112	79.36 246	55.41 61	86.99 94	83.75 199	56.69 307	58.92 290	81.35 299	24.31 409	92.10 65	53.23 306	70.61 228	85.46 268

BH-RMVSNet		70.08 215	68.01 226	76.27 156	84.21 98	51.22 200	87.29 87	79.33 302	58.96 258	63.63 227	86.77 199	33.29 334	90.30 125	44.63 369	73.96 186	87.30 223

UGNet		68.71 249	67.11 253	73.50 259	80.55 215	47.61 319	84.08 213	78.51 321	59.45 240	65.68 183	82.73 270	23.78 411	85.08 331	52.80 312	76.40 143	87.80 209
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
WTY-MVS		77.47 47	77.52 42	77.30 124	88.33 32	46.25 351	88.46 56	90.32 20	71.40 24	72.32 97	91.72 72	53.44 46	92.37 56	66.28 174	75.42 168	93.28 14

XXY-MVS		70.18 210	69.28 206	72.89 275	77.64 286	42.88 396	85.06 173	87.50 78	62.58 182	62.66 239	82.34 284	43.64 179	89.83 139	58.42 253	63.70 297	85.96 258

EC-MVSNet		75.30 101	75.20 86	75.62 179	80.98 197	49.00 264	87.43 80	84.68 176	63.49 161	70.97 124	90.15 116	42.86 193	91.14 90	74.33 104	81.90 74	86.71 242

sss		70.49 207	70.13 190	71.58 319	81.59 179	39.02 423	80.78 317	84.71 175	59.34 244	66.61 168	88.09 167	37.17 273	85.52 320	61.82 220	71.02 224	90.20 131

Test_1112_low_res		67.18 286	66.23 271	70.02 346	78.75 264	41.02 415	83.43 236	73.69 389	57.29 292	58.45 306	82.39 279	45.30 152	80.88 373	50.50 330	66.26 276	88.16 199

1112_ss		70.05 216	69.37 202	72.10 301	80.77 207	42.78 397	85.12 172	76.75 354	59.69 236	61.19 256	92.12 59	47.48 100	83.84 346	53.04 309	68.21 253	89.66 150

ab-mvs-re		7.68 466	10.24 468	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	92.12 59	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

ab-mvs		70.65 204	69.11 209	75.29 199	80.87 203	46.23 354	73.48 389	85.24 141	59.99 230	66.65 166	80.94 302	43.13 189	88.69 192	63.58 203	68.07 254	90.95 105

TR-MVS		69.71 224	67.85 236	75.27 202	82.94 132	48.48 283	87.40 83	80.86 260	57.15 296	64.61 203	87.08 195	32.67 342	89.64 150	46.38 360	71.55 217	87.68 213

MDTV_nov1_ep13_2view						43.62 385	71.13 412		54.95 339	59.29 283		36.76 281		46.33 361		87.32 222

MDTV_nov1_ep13			61.56 332		81.68 171	55.12 73	72.41 400	78.18 327	59.19 249	58.85 293	69.29 427	34.69 318	86.16 301	36.76 404	62.96 310

MIMVSNet1		50.35 422	47.81 422	57.96 435	61.53 458	27.80 474	67.40 427	74.06 384	43.25 431	33.31 471	65.38 444	16.03 456	71.34 448	21.80 466	47.55 426	74.75 426

MIMVSNet		63.12 338	60.29 348	71.61 316	75.92 328	46.65 338	65.15 433	81.94 235	59.14 253	54.65 355	69.47 425	25.74 395	80.63 379	41.03 386	69.56 243	87.55 216

IterMVS-LS		66.63 298	65.36 294	70.42 337	75.10 342	48.90 268	81.45 305	76.69 358	61.05 212	55.71 344	77.10 348	45.86 139	83.65 350	57.44 270	57.88 360	78.70 381
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		70.48 208	69.43 200	73.64 254	77.56 290	48.83 270	83.51 232	77.45 342	63.27 165	62.33 241	85.54 219	43.85 171	83.29 356	57.38 272	74.00 185	88.79 178
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															63.20 306

IterMVS		63.77 331	61.67 330	70.08 343	72.68 375	51.24 199	80.44 323	75.51 368	60.51 224	51.41 381	73.70 387	32.08 349	78.91 396	54.30 298	54.35 391	80.08 371
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		71.99 172	70.31 185	77.01 135	90.65 9	53.44 132	89.37 39	82.97 218	56.33 318	63.56 229	89.47 128	34.02 326	92.15 64	54.05 300	72.41 205	85.43 269

MVS_111021_LR		69.07 237	67.91 228	72.54 287	77.27 297	49.56 246	79.77 336	73.96 386	59.33 246	60.73 261	87.82 177	30.19 367	81.53 367	69.94 145	72.19 210	86.53 245

DP-MVS		59.24 364	56.12 377	68.63 362	88.24 36	50.35 227	82.51 269	64.43 446	41.10 437	46.70 418	78.77 327	24.75 405	88.57 200	22.26 465	56.29 373	66.96 459

ACMMP++															59.38 339

HQP-MVS		72.34 163	71.44 160	75.03 208	79.02 257	51.56 190	88.00 61	83.68 201	65.45 116	64.48 206	85.13 225	37.35 266	88.62 194	66.70 169	73.12 196	84.91 278

QAPM		71.88 176	69.33 204	79.52 45	82.20 157	54.30 112	86.30 116	88.77 44	56.61 311	59.72 271	87.48 187	33.90 328	95.36 14	47.48 352	81.49 78	88.90 173

Vis-MVSNet		70.61 205	69.34 203	74.42 225	80.95 202	48.49 282	86.03 125	77.51 341	58.74 262	65.55 185	87.78 178	34.37 323	85.95 315	52.53 319	80.61 86	88.80 177
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		49.01 425	44.71 429	61.92 419	76.06 321	46.61 340	63.23 442	54.90 463	24.77 475	33.56 467	36.60 484	21.28 428	75.88 429	29.49 437	62.54 314	63.26 469

IS-MVSNet		68.80 247	67.55 242	72.54 287	78.50 273	43.43 388	81.03 310	79.35 300	59.12 254	57.27 327	86.71 200	46.05 128	87.70 246	44.32 372	75.60 166	86.49 247

HyFIR lowres test		69.94 221	67.58 240	77.04 133	77.11 303	57.29 23	81.49 304	79.11 305	58.27 268	58.86 292	80.41 306	42.33 196	86.96 272	61.91 218	68.68 251	86.87 233

EPMVS		68.45 254	65.44 292	77.47 118	84.91 80	56.17 45	71.89 409	81.91 238	61.72 198	60.85 259	72.49 399	36.21 291	87.06 269	47.32 353	71.62 215	89.17 168

PAPM_NR		71.80 178	69.98 194	77.26 128	81.54 182	53.34 137	78.60 351	85.25 140	53.46 353	60.53 264	88.66 144	45.69 143	89.24 165	56.49 279	79.62 104	89.19 167

TAMVS		69.51 232	68.16 225	73.56 258	76.30 316	48.71 276	82.57 264	77.17 347	62.10 190	61.32 255	84.23 242	41.90 205	83.46 353	54.80 296	73.09 198	88.50 193

PAPR		75.20 107	74.13 111	78.41 91	88.31 34	55.10 75	84.31 206	85.66 121	63.76 152	67.55 160	90.73 98	43.48 182	89.40 159	66.36 173	77.03 133	90.73 111

RPSCF		45.77 431	44.13 433	50.68 447	57.67 466	29.66 466	54.92 466	45.25 473	26.69 473	45.92 422	75.92 369	17.43 450	45.70 485	27.44 449	45.95 436	76.67 407

Vis-MVSNet (Re-imp)		65.52 314	65.63 286	65.17 396	77.49 292	30.54 457	75.49 372	77.73 337	59.34 244	52.26 376	86.69 201	49.38 80	80.53 382	37.07 399	75.28 170	84.42 284

test_0402		56.45 389	53.03 393	66.69 382	76.78 309	50.31 229	81.76 287	69.61 427	42.79 433	43.88 427	72.13 411	22.82 418	86.46 292	16.57 479	50.94 407	63.31 468

MVS_111021_HR		76.39 71	75.38 85	79.42 47	85.33 73	56.47 40	88.15 59	84.97 157	65.15 127	66.06 175	89.88 121	43.79 174	92.16 62	75.03 95	80.03 97	89.64 151

CSCG		80.41 15	79.72 16	82.49 6	89.12 26	57.67 16	89.29 45	91.54 5	59.19 249	71.82 105	90.05 118	59.72 11	96.04 11	78.37 67	88.40 14	93.75 8

PatchMatch-RL		56.66 386	53.75 391	65.37 395	77.91 285	45.28 366	69.78 418	60.38 453	41.35 436	47.57 411	73.73 384	16.83 452	76.91 419	36.99 400	59.21 341	73.92 433

API-MVS		74.17 124	72.07 150	80.49 26	90.02 12	58.55 10	87.30 86	84.27 185	57.51 286	65.77 181	87.77 179	41.61 209	95.97 12	51.71 323	82.63 67	86.94 231

Test By Simon												39.38 237

TDRefinement		40.91 436	38.37 440	48.55 453	50.45 479	33.03 449	58.98 457	50.97 468	28.50 469	29.89 474	67.39 434	6.21 484	54.51 476	17.67 477	35.25 461	58.11 471

USDC		54.36 399	51.23 403	63.76 403	64.29 448	37.71 431	62.84 445	73.48 395	56.85 299	35.47 461	71.94 414	9.23 471	78.43 399	38.43 393	48.57 418	75.13 423

EPP-MVSNet		71.14 190	70.07 192	74.33 230	79.18 253	46.52 342	83.81 224	86.49 101	56.32 319	57.95 310	84.90 233	54.23 42	89.14 170	58.14 258	69.65 241	87.33 221

PMMVS		72.98 147	72.05 151	75.78 174	83.57 108	48.60 277	84.08 213	82.85 220	61.62 200	68.24 154	90.33 108	28.35 374	87.78 242	72.71 123	76.69 142	90.95 105

PAPM		76.76 63	76.07 70	78.81 64	80.20 227	59.11 7	86.86 102	86.23 107	68.60 58	70.18 140	88.84 141	51.57 57	87.16 266	65.48 182	86.68 31	90.15 134

ACMMP		70.81 200	69.29 205	75.39 193	81.52 184	51.92 178	83.43 236	83.03 216	56.67 308	58.80 294	88.91 139	31.92 352	88.58 197	65.89 179	73.39 193	85.67 263
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CNLPA		60.59 357	58.44 361	67.05 378	79.21 251	47.26 328	79.75 337	64.34 447	42.46 435	51.90 379	83.94 246	27.79 381	75.41 431	37.12 397	59.49 338	78.47 385

PatchmatchNet		67.07 291	63.63 313	77.40 121	83.10 122	58.03 12	72.11 407	77.77 336	58.85 259	59.37 279	70.83 418	37.84 252	84.93 333	42.96 378	69.83 239	89.26 163
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		77.49 46	77.00 51	78.95 59	85.33 73	50.69 211	88.57 55	88.59 54	58.14 270	73.60 75	93.31 30	43.14 188	93.79 29	73.81 111	88.53 13	92.37 35

F-COLMAP		55.96 394	53.65 392	62.87 412	72.76 374	42.77 398	74.70 378	70.37 421	40.03 438	41.11 444	79.36 320	17.77 447	73.70 439	32.80 426	53.96 393	72.15 445

ANet_high		34.39 445	29.59 451	48.78 452	30.34 496	22.28 481	55.53 463	63.79 448	38.11 445	15.47 488	36.56 485	6.94 478	59.98 466	13.93 483	5.64 499	64.08 466

wuyk23d		9.11 465	8.77 469	10.15 481	40.18 488	16.76 494	20.28 492	1.01 505	2.58 498	2.66 500	0.98 500	0.23 504	12.49 500	4.08 499	6.90 497	1.19 497

OMC-MVS		65.97 310	65.06 300	68.71 361	72.97 371	42.58 401	78.61 350	75.35 371	54.72 341	59.31 281	86.25 207	33.30 333	77.88 410	57.99 259	67.05 262	85.66 264

MG-MVS		78.42 31	76.99 52	82.73 3	93.17 1	64.46 1	89.93 29	88.51 56	64.83 129	73.52 77	88.09 167	48.07 87	92.19 61	62.24 215	84.53 57	91.53 73

AdaColmap		67.86 265	65.48 289	75.00 210	88.15 38	54.99 80	86.10 122	76.63 359	49.30 384	57.80 313	86.65 203	29.39 371	88.94 183	45.10 366	70.21 236	81.06 358

uanet		0.00 470	0.00 473	0.00 485	0.00 507	0.00 509	0.00 496	0.00 507	0.00 501	0.00 504	0.00 503	0.00 505	0.00 502	0.00 502	0.00 500	0.00 500

ITE_SJBPF				51.84 446	58.03 464	31.94 455		53.57 467	36.67 451	41.32 442	75.23 373	11.17 466	51.57 479	25.81 454	48.04 422	72.02 447

DeepMVS_CX				13.10 480	21.34 504	8.99 502		10.02 504	10.59 492	7.53 497	30.55 490	1.82 497	14.55 499	6.83 493	7.52 495	15.75 493

TinyColmap		48.15 427	44.49 431	59.13 432	65.73 438	38.04 429	63.34 441	62.86 451	38.78 441	29.48 475	67.23 435	6.46 482	73.30 441	24.59 457	41.90 446	66.04 462

MAR-MVS		76.76 63	75.60 78	80.21 34	90.87 8	54.68 104	89.14 46	89.11 33	62.95 171	70.54 136	92.33 56	41.05 213	94.95 18	57.90 264	86.55 33	91.00 102
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
LF4IMVS		33.04 448	32.55 448	34.52 468	40.96 487	22.03 482	44.45 476	35.62 486	20.42 478	28.12 478	62.35 451	5.03 487	31.88 498	21.61 468	34.42 463	49.63 479

MSDG		59.44 362	55.14 383	72.32 297	74.69 347	50.71 210	74.39 381	73.58 390	44.44 424	43.40 431	77.52 339	19.45 436	90.87 103	31.31 431	57.49 364	75.38 419

LS3D		56.40 390	53.82 390	64.12 401	81.12 194	45.69 364	73.42 390	66.14 438	35.30 460	43.24 433	79.88 312	22.18 423	79.62 394	19.10 474	64.00 294	67.05 458

CLD-MVS		75.60 98	75.39 84	76.24 157	80.69 209	52.40 163	90.69 23	86.20 108	74.40 6	65.01 193	88.93 138	42.05 202	90.58 113	76.57 81	73.96 186	85.73 262
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		35.40 443	33.67 447	40.57 462	46.34 485	28.74 472	41.05 479	57.05 460	20.37 479	22.27 484	53.38 473	6.87 479	44.94 487	8.62 488	47.11 430	48.01 480

Gipuma		27.47 451	24.26 456	37.12 467	60.55 462	29.17 469	11.68 494	60.00 454	14.18 486	10.52 495	15.12 496	2.20 495	63.01 461	8.39 489	35.65 459	19.18 492
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark