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.

DeepC-MVS_fast	96.59 1	98.81 26	98.54 32	99.62 21	99.90 46	98.85 36	99.24 291	98.47 139	98.14 15	99.08 106	99.91 18	93.09 130	100.00 1	99.04 83	99.99 21	100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS	95.94 2	97.71 106	98.98 13	93.92 348	99.63 89	81.76 440	99.96 52	98.56 112	99.47 1	99.19 100	99.99 1	94.16 99	100.00 1	99.92 16	99.93 65	100.00 1

PLC	95.54 3	97.93 82	97.89 82	98.05 163	99.82 64	94.77 236	99.92 99	98.46 141	93.93 177	97.20 195	99.27 160	95.44 54	99.97 63	97.41 175	99.51 116	99.41 192
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
DeepC-MVS	94.51 4	96.92 148	96.40 157	98.45 136	99.16 120	95.90 182	99.66 215	98.06 233	96.37 86	94.37 270	99.49 135	83.29 298	99.90 111	97.63 172	99.61 103	99.55 159
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PCF-MVS	94.20 5	95.18 225	94.10 244	98.43 138	98.55 175	95.99 180	97.91 399	97.31 323	90.35 324	89.48 338	99.22 168	85.19 274	99.89 116	90.40 330	98.47 170	99.41 192
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS	92.85 6	94.99 231	93.94 252	98.16 153	97.72 240	95.69 194	99.99 5	98.81 67	94.28 160	92.70 292	96.90 318	95.08 61	99.17 202	96.07 214	73.88 436	99.60 148
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
HY-MVS	92.50 7	97.79 98	97.17 121	99.63 18	98.98 136	99.32 9	97.49 406	99.52 14	95.69 107	98.32 154	97.41 301	93.32 121	99.77 148	98.08 148	95.75 257	99.81 108

TAPA-MVS	92.12 8	94.42 255	93.60 261	96.90 240	99.33 108	91.78 321	99.78 167	98.00 238	89.89 335	94.52 264	99.47 136	91.97 164	99.18 201	69.90 451	99.52 113	99.73 119
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP	92.05 9	92.74 301	92.42 300	93.73 353	95.91 342	88.72 384	99.81 160	97.53 294	94.13 164	87.00 383	98.23 277	74.07 390	98.47 264	96.22 213	88.86 323	93.99 376
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
ACMM	91.95 10	92.88 298	92.52 298	93.98 347	95.75 350	89.08 379	99.77 172	97.52 296	93.00 217	89.95 322	97.99 286	76.17 373	98.46 267	93.63 275	88.87 322	94.39 336
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
3Dnovator+	91.53 11	96.31 183	95.24 209	99.52 32	96.88 311	98.64 58	99.72 196	98.24 209	95.27 119	88.42 365	98.98 196	82.76 302	99.94 92	97.10 187	99.83 81	99.96 74

3Dnovator	91.47 12	96.28 186	95.34 205	99.08 81	96.82 314	97.47 112	99.45 262	98.81 67	95.52 113	89.39 339	99.00 193	81.97 308	99.95 84	97.27 179	99.83 81	99.84 103

PVSNet	91.05 13	97.13 134	96.69 144	98.45 136	99.52 98	95.81 185	99.95 71	99.65 12	94.73 134	99.04 112	99.21 171	84.48 288	99.95 84	94.92 236	98.74 162	99.58 155

COLMAP_ROB	90.47 14	92.18 315	91.49 317	94.25 336	99.00 133	88.04 395	98.42 378	96.70 401	82.30 429	88.43 363	99.01 191	76.97 361	99.85 128	86.11 381	96.50 234	94.86 323
Johannes L. SchÃ¶nberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
OpenMVS	90.15 15	94.77 239	93.59 262	98.33 144	96.07 336	97.48 111	99.56 240	98.57 106	90.46 321	86.51 389	98.95 205	78.57 350	99.94 92	93.86 263	99.74 90	97.57 303

ACMH+	89.98 16	90.35 353	89.54 352	92.78 380	95.99 339	86.12 408	98.81 347	97.18 342	89.38 339	83.14 415	97.76 295	68.42 415	98.43 269	89.11 344	86.05 352	93.78 391

ACMH	89.72 17	90.64 346	89.63 349	93.66 359	95.64 359	88.64 387	98.55 367	97.45 301	89.03 344	81.62 422	97.61 296	69.75 409	98.41 272	89.37 341	87.62 344	93.92 382
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LTVRE_ROB	88.28 18	90.29 356	89.05 363	94.02 343	95.08 368	90.15 362	97.19 413	97.43 303	84.91 410	83.99 411	97.06 313	74.00 391	98.28 291	84.08 394	87.71 340	93.62 398
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
PVSNet_0	88.03 19	91.80 323	90.27 337	96.38 260	98.27 200	90.46 355	99.94 89	99.61 13	93.99 173	86.26 395	97.39 303	71.13 405	99.89 116	98.77 104	67.05 455	98.79 261

OpenMVS_ROB	79.82 20	83.77 411	81.68 414	90.03 413	88.30 451	82.82 430	98.46 372	95.22 438	73.92 455	76.00 448	91.29 439	55.00 451	96.94 366	68.40 454	88.51 331	90.34 441

CMPMVS	61.59 21	84.75 404	85.14 396	83.57 437	90.32 442	62.54 465	96.98 419	97.59 288	74.33 454	69.95 458	96.66 327	64.17 432	98.32 286	87.88 360	88.41 332	89.84 448
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVE	53.74 22	51.54 441	47.86 445	62.60 456	59.56 480	50.93 475	79.41 471	77.69 479	35.69 475	36.27 477	61.76 476	5.79 484	69.63 475	37.97 475	36.61 472	67.24 470
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVS	49.05 23	53.75 439	51.34 443	60.97 457	40.80 483	34.68 484	74.82 472	89.62 472	37.55 473	28.67 479	72.12 468	7.09 482	81.63 473	43.17 474	68.21 452	66.59 471
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E2		96.36 179	95.95 179	97.60 200	97.41 268	94.52 242	99.71 199	97.33 317	93.20 205	97.02 201	99.07 184	85.37 272	98.82 227	97.27 179	97.14 215	99.46 180

MED-MVS test				99.60 23	99.96 8	98.79 41	99.97 38	98.88 54	96.36 87	99.07 108	99.93 11		100.00 1	99.98 9	99.96 46	99.99 24

MED-MVS		99.15 8	99.00 12	99.60 23	99.96 8	98.79 41	99.97 38	98.88 54	95.89 100	99.07 108	99.93 11	97.36 17	100.00 1	99.98 9	99.96 46	99.99 24

E3		96.36 179	95.95 179	97.60 200	97.37 274	94.52 242	99.71 199	97.33 317	93.18 207	97.02 201	99.07 184	85.45 270	98.82 227	97.27 179	97.14 215	99.46 180

TestfortrainingZip a		99.09 10	98.87 19	99.76 10	99.96 8	99.27 18	99.97 38	98.88 54	96.36 87	99.07 108	99.93 11	97.36 17	100.00 1	98.32 132	99.96 46	100.00 1

TestfortrainingZip							99.97 38

fmvsm_s_conf0.5_n_10		98.24 69	97.90 80	99.26 54	99.24 114	97.88 91	99.99 5	98.76 73	98.20 9	99.92 4	99.74 86	85.97 259	99.94 92	99.72 45	99.53 112	99.96 74

viewdifsd2359ckpt07		95.83 203	95.42 201	97.07 233	97.40 270	93.04 289	99.60 230	97.24 335	92.39 253	96.09 235	99.14 179	83.07 301	98.93 219	97.02 189	96.87 228	99.23 225

viewdifsd2359ckpt09		96.21 189	95.77 188	97.53 207	97.69 244	94.50 244	99.78 167	97.23 337	92.88 222	96.58 217	99.26 164	84.85 279	98.66 254	96.61 204	97.02 224	99.43 189

viewdifsd2359ckpt13		96.19 190	95.77 188	97.45 213	97.62 252	94.40 250	99.70 206	97.23 337	92.76 231	96.63 214	99.05 187	84.96 278	98.64 255	96.65 203	97.35 204	99.31 211

viewcassd2359sk11		96.59 166	96.23 161	97.66 192	97.63 251	94.70 237	99.77 172	97.33 317	93.41 198	97.34 190	99.17 175	86.72 245	98.83 226	97.40 176	97.32 206	99.46 180

viewdifsd2359ckpt11		94.09 265	93.63 258	95.46 287	96.68 323	88.92 380	99.62 223	97.12 352	93.07 214	95.73 245	99.22 168	77.05 357	98.88 222	96.52 208	87.69 343	98.58 271

viewmacassd2359aftdt		95.93 198	95.45 199	97.36 223	97.09 292	94.12 260	99.57 237	97.26 331	93.05 216	96.50 221	99.17 175	82.76 302	98.68 249	96.61 204	97.04 221	99.28 218

viewmsd2359difaftdt		94.09 265	93.64 257	95.46 287	96.68 323	88.92 380	99.62 223	97.13 351	93.07 214	95.73 245	99.22 168	77.05 357	98.89 221	96.52 208	87.70 342	98.58 271

diffmvs_AUTHOR		96.75 157	96.41 156	97.79 181	97.20 287	95.46 202	99.69 209	97.15 347	94.46 144	98.78 124	99.21 171	85.64 264	98.77 235	98.27 136	97.31 207	99.13 233

FE-MVSNET		81.05 419	78.81 426	87.79 429	81.98 463	83.70 423	98.23 387	91.78 466	81.27 433	74.29 453	87.44 456	60.92 445	90.67 460	64.92 462	68.43 450	89.01 456

fmvsm_l_conf0.5_n_9		98.55 40	98.23 51	99.49 36	99.10 123	98.50 64	99.99 5	98.70 79	98.14 15	99.94 1	99.68 110	89.02 213	99.98 50	99.89 21	99.61 103	99.99 24

mamba_0408		94.98 232	94.09 245	97.64 194	97.14 288	95.31 213	93.48 452	97.08 363	90.48 319	94.40 267	98.62 245	84.49 286	98.67 251	93.99 259	97.18 212	98.93 250

icg_test_0407_2		95.04 229	94.78 229	95.84 276	96.97 300	91.64 328	98.63 364	97.12 352	92.33 256	95.60 248	98.88 212	85.65 262	96.56 386	92.12 294	95.70 260	99.32 207

SSM_04072		94.77 239	94.09 245	96.82 242	97.14 288	95.31 213	93.48 452	97.08 363	90.48 319	94.40 267	98.62 245	84.49 286	96.21 402	93.99 259	97.18 212	98.93 250

SSM_0407		95.62 213	94.95 222	97.61 199	97.14 288	95.31 213	99.00 320	97.25 332	90.81 308	94.40 267	98.83 226	84.74 281	98.58 258	95.24 228	97.18 212	98.93 250

viewmambaseed2359dif		95.92 199	95.55 198	97.04 234	97.38 272	93.41 280	99.78 167	96.97 378	91.14 298	96.58 217	99.27 160	84.85 279	98.75 239	96.87 198	97.12 217	98.97 248

IMVS_0407		95.21 224	94.80 228	96.46 255	96.97 300	91.64 328	98.81 347	97.12 352	92.33 256	95.60 248	98.88 212	85.65 262	98.42 270	92.12 294	95.70 260	99.32 207

viewmanbaseed2359cas		96.45 173	96.07 167	97.59 203	97.55 258	94.59 239	99.70 206	97.33 317	93.62 191	97.00 204	99.32 152	85.57 266	98.71 244	97.26 182	97.33 205	99.47 178

IMVS_0404		93.83 270	93.17 280	95.80 278	96.97 300	91.64 328	97.78 403	97.12 352	92.33 256	90.87 311	98.88 212	76.78 364	96.43 392	92.12 294	95.70 260	99.32 207

SSM_0404		95.75 205	95.16 213	97.50 211	97.53 260	95.39 208	99.11 301	97.25 332	90.81 308	95.27 257	98.83 226	84.74 281	98.67 251	95.24 228	97.69 193	98.45 274

IMVS_0403		95.25 222	94.81 227	96.58 252	96.97 300	91.64 328	98.97 327	97.12 352	92.33 256	95.43 253	98.88 212	85.78 261	98.79 232	92.12 294	95.70 260	99.32 207

SD_0403		92.63 306	93.38 273	90.40 409	97.32 280	77.91 452	97.75 404	98.03 237	91.89 271	90.83 312	98.29 275	82.00 307	93.79 442	88.51 352	95.75 257	99.52 169

fmvsm_s_conf0.5_n_9		98.15 73	98.02 68	98.55 123	99.28 111	95.84 184	99.99 5	98.57 106	98.17 12	99.93 2	99.74 86	87.04 241	99.97 63	99.86 26	99.59 107	99.83 104

ME-MVS		99.07 12	98.89 17	99.59 26	99.93 27	98.79 41	99.95 71	98.80 71	95.89 100	99.28 95	99.93 11	96.28 37	99.98 50	99.98 9	99.96 46	99.99 24

NormalMVS		97.90 84	97.85 84	98.04 164	99.86 57	95.39 208	99.61 227	97.78 263	96.52 75	98.61 137	99.31 155	92.73 141	99.67 166	96.77 200	99.48 120	99.06 241

lecture		98.67 33	98.46 36	99.28 52	99.86 57	97.88 91	99.97 38	99.25 30	96.07 95	99.79 34	99.70 99	92.53 149	99.98 50	99.51 58	99.48 120	99.97 66

SymmetryMVS		97.64 109	97.46 103	98.17 152	98.74 160	95.39 208	99.61 227	99.26 29	96.52 75	98.61 137	99.31 155	92.73 141	99.67 166	96.77 200	95.63 264	99.45 185

Elysia		94.50 251	93.38 273	97.85 177	96.49 327	96.70 144	98.98 322	97.78 263	90.81 308	96.19 232	98.55 255	73.63 393	98.98 213	89.41 339	98.56 166	97.88 290

StellarMVS		94.50 251	93.38 273	97.85 177	96.49 327	96.70 144	98.98 322	97.78 263	90.81 308	96.19 232	98.55 255	73.63 393	98.98 213	89.41 339	98.56 166	97.88 290

KinetiMVS		96.10 191	95.29 208	98.53 129	97.08 293	97.12 127	99.56 240	98.12 229	94.78 131	98.44 146	98.94 207	80.30 334	99.39 189	91.56 306	98.79 160	99.06 241

LuminaMVS		96.63 164	96.21 164	97.87 176	95.58 362	96.82 140	99.12 299	97.67 273	94.47 143	97.88 173	98.31 273	87.50 232	98.71 244	98.07 149	97.29 208	98.10 286

VortexMVS		94.11 263	93.50 266	95.94 271	97.70 243	96.61 151	99.35 276	97.18 342	93.52 194	89.57 336	95.74 355	87.55 231	96.97 364	95.76 222	85.13 361	94.23 349

AstraMVS		96.57 168	96.46 154	96.91 238	96.79 318	92.50 304	99.90 113	97.38 309	96.02 97	97.79 178	99.32 152	86.36 253	98.99 212	98.26 137	96.33 240	99.23 225

guyue		97.15 133	96.82 136	98.15 156	97.56 257	96.25 170	99.71 199	97.84 258	95.75 105	98.13 164	98.65 240	87.58 230	98.82 227	98.29 135	97.91 191	99.36 198

sc_t1		85.01 401	82.46 411	92.67 381	92.44 419	83.09 429	97.39 409	95.72 425	65.06 461	85.64 401	96.16 343	49.50 459	97.34 335	84.86 391	75.39 433	97.57 303

tt0320-xc		82.94 414	80.35 421	90.72 404	92.90 410	83.54 426	96.85 423	94.73 446	63.12 463	79.85 433	93.77 421	49.43 460	95.46 420	80.98 416	71.54 441	93.16 409

tt0320		83.56 413	81.15 416	90.77 402	92.77 415	83.58 425	96.83 424	95.52 432	63.26 462	81.36 424	92.54 431	53.26 454	95.77 415	80.45 418	74.38 435	92.96 413

fmvsm_s_conf0.5_n_8		98.38 57	98.05 66	99.35 49	99.20 116	98.12 76	99.98 20	98.81 67	98.22 7	99.80 25	99.71 96	87.37 236	99.97 63	99.91 19	99.48 120	99.97 66

fmvsm_s_conf0.5_n_7		97.70 107	97.74 88	97.59 203	98.44 186	95.16 225	99.97 38	98.65 87	97.95 23	99.62 59	99.78 66	86.09 256	99.94 92	99.69 49	99.50 118	97.66 297

fmvsm_s_conf0.5_n_6		98.27 63	97.96 75	99.23 57	97.66 248	98.11 77	99.98 20	98.64 90	97.85 26	99.87 12	99.72 93	88.86 216	99.93 102	99.64 53	99.36 134	99.63 141

fmvsm_s_conf0.5_n_5		98.08 77	97.71 91	99.17 65	98.67 164	97.69 102	99.99 5	98.57 106	97.40 39	99.89 9	99.69 103	85.99 258	99.96 75	99.80 31	99.40 131	99.85 102

fmvsm_s_conf0.5_n_4		97.75 101	97.86 83	97.42 217	99.01 129	94.69 238	99.97 38	98.76 73	97.91 24	99.87 12	99.76 71	86.70 248	99.93 102	99.67 51	99.12 147	97.64 298

SSC-MVS3.2		89.59 370	88.66 370	92.38 383	94.29 383	86.12 408	99.49 253	97.66 276	90.28 328	88.63 358	95.18 388	64.46 431	96.88 371	85.30 387	82.66 378	94.14 363

testing3-2		97.72 105	97.43 108	98.60 117	98.55 175	97.11 129	100.00 1	99.23 31	93.78 184	97.90 170	98.73 232	95.50 52	99.69 162	98.53 120	94.63 279	98.99 247

myMVS_eth3d28		97.86 87	97.59 99	98.68 109	98.50 182	97.26 119	99.92 99	98.55 118	93.79 183	98.26 158	98.75 230	95.20 57	99.48 184	98.93 91	96.40 237	99.29 216

UWE-MVS-28		95.95 196	96.49 151	94.34 333	98.51 180	89.99 365	99.39 269	98.57 106	93.14 210	97.33 191	98.31 273	93.44 116	94.68 433	93.69 274	95.98 247	98.34 280

fmvsm_l_conf0.5_n_3		98.41 53	98.08 64	99.39 45	99.12 122	98.29 69	99.98 20	98.64 90	98.14 15	99.86 14	99.76 71	87.99 225	99.97 63	99.72 45	99.54 110	99.91 94

fmvsm_s_conf0.5_n_3		97.95 80	97.66 93	98.81 100	98.99 134	98.07 79	99.98 20	98.81 67	98.18 11	99.89 9	99.70 99	84.15 291	99.97 63	99.76 39	99.50 118	98.39 277

fmvsm_s_conf0.5_n_2		97.59 111	97.28 114	98.53 129	99.01 129	98.15 71	99.98 20	98.59 102	98.17 12	99.75 39	99.63 120	81.83 311	99.94 92	99.78 34	98.79 160	97.51 306

fmvsm_s_conf0.1_n_2		97.25 127	96.85 134	98.43 138	98.08 214	98.08 78	99.92 99	97.76 267	98.05 19	99.65 52	99.58 126	80.88 324	99.93 102	99.59 55	98.17 179	97.29 307

GDP-MVS		97.88 85	97.59 99	98.75 105	97.59 255	97.81 95	99.95 71	97.37 312	94.44 148	99.08 106	99.58 126	97.13 25	99.08 208	94.99 233	98.17 179	99.37 196

BP-MVS1		98.33 59	98.18 56	98.81 100	97.44 266	97.98 85	99.96 52	98.17 218	94.88 128	98.77 126	99.59 123	97.59 7	99.08 208	98.24 138	98.93 153	99.36 198

reproduce_monomvs		95.38 219	95.07 217	96.32 262	99.32 110	96.60 152	99.76 178	98.85 62	96.65 71	87.83 371	96.05 350	99.52 1	98.11 302	96.58 206	81.07 395	94.25 347

mmtdpeth		88.52 379	87.75 381	90.85 400	95.71 354	83.47 428	98.94 330	94.85 442	88.78 355	97.19 196	89.58 446	63.29 435	98.97 215	98.54 118	62.86 463	90.10 445

reproduce_model		98.75 30	98.66 26	99.03 84	99.71 82	97.10 130	99.73 192	98.23 211	97.02 57	99.18 101	99.90 22	94.54 81	99.99 39	99.77 36	99.90 73	99.99 24

reproduce-ours		98.78 27	98.67 24	99.09 79	99.70 84	97.30 117	99.74 185	98.25 207	97.10 52	99.10 104	99.90 22	94.59 77	99.99 39	99.77 36	99.91 71	99.99 24

our_new_method		98.78 27	98.67 24	99.09 79	99.70 84	97.30 117	99.74 185	98.25 207	97.10 52	99.10 104	99.90 22	94.59 77	99.99 39	99.77 36	99.91 71	99.99 24

mmdepth		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

monomultidepth		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

mvs5depth		84.87 402	82.90 408	90.77 402	85.59 457	84.84 418	91.10 463	93.29 460	83.14 422	85.07 405	94.33 415	62.17 439	97.32 338	78.83 429	72.59 440	90.14 444

MVStest1		85.03 400	82.76 409	91.83 391	92.95 409	89.16 378	98.57 366	94.82 443	71.68 458	68.54 461	95.11 391	83.17 300	95.66 417	74.69 443	65.32 458	90.65 439

ttmdpeth		88.23 383	87.06 386	91.75 393	89.91 446	87.35 400	98.92 335	95.73 424	87.92 370	84.02 410	96.31 338	68.23 417	96.84 373	86.33 378	76.12 429	91.06 434

WBMVS		94.52 250	94.03 248	95.98 269	98.38 189	96.68 147	99.92 99	97.63 278	90.75 315	89.64 333	95.25 386	96.77 27	96.90 368	94.35 253	83.57 373	94.35 340

dongtai		91.55 329	91.13 322	92.82 378	98.16 209	86.35 406	99.47 257	98.51 130	83.24 421	85.07 405	97.56 297	90.33 193	94.94 429	76.09 440	91.73 304	97.18 309

kuosan		93.17 290	92.60 292	94.86 309	98.40 188	89.54 373	98.44 374	98.53 125	84.46 413	88.49 359	97.92 289	90.57 188	97.05 356	83.10 402	93.49 296	97.99 288

MVSMamba_PlusPlus		97.83 91	97.45 105	98.99 89	98.60 171	98.15 71	99.58 234	97.74 268	90.34 325	99.26 97	98.32 271	94.29 93	99.23 194	99.03 86	99.89 74	99.58 155

MGCFI-Net		97.00 142	96.22 163	99.34 50	98.86 152	98.80 40	99.67 214	97.30 324	94.31 157	97.77 179	99.41 144	86.36 253	99.50 178	98.38 127	93.90 293	99.72 121

testing91		97.16 132	96.90 130	97.97 166	98.35 194	95.67 195	99.91 107	98.42 167	92.91 221	97.33 191	98.72 233	94.81 71	99.21 196	96.98 192	94.63 279	99.03 244

testing11		97.48 115	97.27 115	98.10 159	98.36 192	96.02 179	99.92 99	98.45 142	93.45 197	98.15 163	98.70 235	95.48 53	99.22 195	97.85 161	95.05 276	99.07 240

testing99		97.17 131	96.91 129	97.95 167	98.35 194	95.70 192	99.91 107	98.43 155	92.94 219	97.36 189	98.72 233	94.83 70	99.21 196	97.00 190	94.64 278	98.95 249

UBG		97.84 90	97.69 92	98.29 147	98.38 189	96.59 154	99.90 113	98.53 125	93.91 179	98.52 141	98.42 266	96.77 27	99.17 202	98.54 118	96.20 241	99.11 236

UWE-MVS		96.79 152	96.72 142	97.00 235	98.51 180	93.70 271	99.71 199	98.60 100	92.96 218	97.09 198	98.34 270	96.67 33	98.85 225	92.11 298	96.50 234	98.44 275

ETVMVS		97.03 141	96.64 145	98.20 151	98.67 164	97.12 127	99.89 123	98.57 106	91.10 300	98.17 162	98.59 248	93.86 108	98.19 298	95.64 223	95.24 274	99.28 218

sasdasda		97.09 137	96.32 158	99.39 45	98.93 141	98.95 28	99.72 196	97.35 313	94.45 145	97.88 173	99.42 140	86.71 246	99.52 174	98.48 122	93.97 291	99.72 121

testing222		97.08 140	96.75 140	98.06 162	98.56 172	96.82 140	99.85 143	98.61 98	92.53 246	98.84 120	98.84 225	93.36 118	98.30 288	95.84 219	94.30 286	99.05 243

WB-MVSnew		92.90 297	92.77 289	93.26 368	96.95 305	93.63 273	99.71 199	98.16 223	91.49 283	94.28 272	98.14 279	81.33 318	96.48 389	79.47 423	95.46 267	89.68 449

fmvsm_l_conf0.5_n_a		99.00 18	98.91 15	99.28 52	99.21 115	97.91 90	99.98 20	98.85 62	98.25 5	99.92 4	99.75 79	94.72 74	99.97 63	99.87 24	99.64 96	99.95 82

fmvsm_l_conf0.5_n		98.94 19	98.84 20	99.25 55	99.17 119	97.81 95	99.98 20	98.86 59	98.25 5	99.90 6	99.76 71	94.21 97	99.97 63	99.87 24	99.52 113	99.98 56

fmvsm_s_conf0.1_n_a		97.09 137	96.90 130	97.63 197	95.65 358	94.21 257	99.83 155	98.50 136	96.27 90	99.65 52	99.64 117	84.72 283	99.93 102	99.04 83	98.84 157	98.74 264

fmvsm_s_conf0.1_n		97.30 124	97.21 118	97.60 200	97.38 272	94.40 250	99.90 113	98.64 90	96.47 79	99.51 75	99.65 116	84.99 277	99.93 102	99.22 74	99.09 148	98.46 273

fmvsm_s_conf0.5_n_a		97.73 104	97.72 89	97.77 185	98.63 170	94.26 255	99.96 52	98.92 49	97.18 51	99.75 39	99.69 103	87.00 243	99.97 63	99.46 63	98.89 154	99.08 239

fmvsm_s_conf0.5_n		97.80 96	97.85 84	97.67 191	99.06 126	94.41 248	99.98 20	98.97 43	97.34 41	99.63 56	99.69 103	87.27 237	99.97 63	99.62 54	99.06 149	98.62 269

MM		98.83 24	98.53 33	99.76 10	99.59 91	99.33 8	99.99 5	99.76 6	98.39 4	99.39 87	99.80 58	90.49 191	99.96 75	99.89 21	99.43 128	99.98 56

WAC-MVS						90.97 340								86.10 382

Syy-MVS		90.00 363	90.63 329	88.11 428	97.68 245	74.66 456	99.71 199	98.35 189	90.79 312	92.10 298	98.67 237	79.10 345	93.09 448	63.35 463	95.95 250	96.59 314

test_fmvsmconf0.1_n		97.74 102	97.44 106	98.64 114	95.76 348	96.20 172	99.94 89	98.05 235	98.17 12	98.89 119	99.42 140	87.65 228	99.90 111	99.50 60	99.60 106	99.82 106

test_fmvsmconf0.01_n		96.39 177	95.74 190	98.32 145	91.47 433	95.56 199	99.84 148	97.30 324	97.74 29	97.89 172	99.35 151	79.62 338	99.85 128	99.25 73	99.24 140	99.55 159

myMVS_eth3d		94.46 254	94.76 230	93.55 361	97.68 245	90.97 340	99.71 199	98.35 189	90.79 312	92.10 298	98.67 237	92.46 153	93.09 448	87.13 369	95.95 250	96.59 314

testing3		93.92 268	94.23 241	92.99 375	97.54 259	90.23 359	99.99 5	99.16 33	90.57 317	91.33 306	98.63 244	92.99 132	92.52 452	82.46 406	95.39 270	96.22 319

SSC-MVS		75.42 428	76.40 431	72.49 452	80.68 467	53.62 474	97.42 407	94.06 453	80.42 437	68.75 460	90.14 445	76.54 368	81.66 472	33.25 477	66.34 457	82.19 463

test_fmvsmconf_n		98.43 51	98.32 47	98.78 102	98.12 213	96.41 159	99.99 5	98.83 66	98.22 7	99.67 50	99.64 117	91.11 177	99.94 92	99.67 51	99.62 99	99.98 56

WB-MVS		76.28 427	77.28 429	73.29 448	81.18 465	54.68 473	97.87 400	94.19 451	81.30 432	69.43 459	90.70 443	77.02 360	82.06 471	35.71 476	68.11 453	83.13 462

test_fmvsmvis_n_1920		97.67 108	97.59 99	97.91 173	97.02 297	95.34 211	99.95 71	98.45 142	97.87 25	97.02 201	99.59 123	89.64 201	99.98 50	99.41 67	99.34 136	98.42 276

dmvs_re		93.20 289	93.15 281	93.34 364	96.54 326	83.81 422	98.71 356	98.51 130	91.39 292	92.37 296	98.56 253	78.66 349	97.83 318	93.89 262	89.74 310	98.38 278

SDMVSNet		94.80 236	93.96 251	97.33 226	98.92 144	95.42 205	99.59 232	98.99 40	92.41 251	92.55 294	97.85 292	75.81 376	98.93 219	97.90 159	91.62 306	97.64 298

dmvs_testset		83.79 410	86.07 391	76.94 444	92.14 423	48.60 479	96.75 425	90.27 469	89.48 338	78.65 437	98.55 255	79.25 341	86.65 467	66.85 457	82.69 377	95.57 322

sd_testset		93.55 282	92.83 286	95.74 280	98.92 144	90.89 345	98.24 385	98.85 62	92.41 251	92.55 294	97.85 292	71.07 406	98.68 249	93.93 261	91.62 306	97.64 298

test_fmvsm_n_1920		98.44 49	98.61 30	97.92 171	99.27 113	95.18 223	100.00 1	98.90 50	98.05 19	99.80 25	99.73 90	92.64 144	99.99 39	99.58 56	99.51 116	98.59 270

test_cas_vis1_n_1920		96.59 166	96.23 161	97.65 193	98.22 203	94.23 256	99.99 5	97.25 332	97.77 28	99.58 67	99.08 182	77.10 356	99.97 63	97.64 171	99.45 126	98.74 264

test_vis1_n_1920		95.44 217	95.31 206	95.82 277	98.50 182	88.74 383	99.98 20	97.30 324	97.84 27	99.85 17	99.19 173	66.82 422	99.97 63	98.82 100	99.46 125	98.76 262

test_vis1_n		93.61 281	93.03 283	95.35 291	95.86 343	86.94 403	99.87 129	96.36 412	96.85 61	99.54 70	98.79 228	52.41 456	99.83 138	98.64 113	98.97 152	99.29 216

test_fmvs1_n		94.25 262	94.36 237	93.92 348	97.68 245	83.70 423	99.90 113	96.57 406	97.40 39	99.67 50	98.88 212	61.82 441	99.92 108	98.23 139	99.13 145	98.14 285

mvsany_test1		97.82 94	97.90 80	97.55 205	98.77 158	93.04 289	99.80 164	97.93 246	96.95 60	99.61 66	99.68 110	90.92 181	99.83 138	99.18 75	98.29 177	99.80 110

APD_test1		81.15 418	80.92 418	81.86 440	92.45 418	59.76 469	96.04 438	93.61 458	73.29 456	77.06 443	96.64 329	44.28 464	96.16 404	72.35 447	82.52 379	89.67 450

test_vis1_rt		86.87 390	86.05 392	89.34 417	96.12 334	78.07 451	99.87 129	83.54 477	92.03 268	78.21 440	89.51 447	45.80 462	99.91 109	96.25 212	93.11 302	90.03 446

test_vis3_rt		68.82 430	66.69 435	75.21 447	76.24 472	60.41 468	96.44 429	68.71 482	75.13 452	50.54 473	69.52 471	16.42 480	96.32 397	80.27 420	66.92 456	68.89 469

test_fmvs2		89.47 372	89.70 348	88.77 424	94.54 377	75.74 453	99.83 155	94.70 448	94.71 135	91.08 307	96.82 326	54.46 452	97.78 321	92.87 286	88.27 333	92.80 417

test_fmvs1		95.35 220	95.68 194	94.36 332	98.99 134	84.98 416	99.96 52	96.65 403	97.60 33	99.73 44	98.96 200	71.58 401	99.93 102	98.31 133	99.37 133	98.17 282

test_fmvs3		79.99 424	80.17 422	79.45 442	84.02 460	62.83 463	99.05 314	93.49 459	88.29 366	80.06 432	86.65 459	28.09 470	88.00 463	88.63 347	73.27 438	87.54 459

mvsany_test3		82.12 416	81.14 417	85.06 435	81.87 464	70.41 459	97.09 416	92.14 463	91.27 294	77.84 441	88.73 450	39.31 465	95.49 418	90.75 322	71.24 442	89.29 454

testf1		68.38 432	66.92 433	72.78 450	78.80 469	50.36 476	90.95 464	87.35 475	55.47 466	58.95 465	88.14 452	20.64 475	87.60 464	57.28 468	64.69 459	80.39 465

APD_test2		68.38 432	66.92 433	72.78 450	78.80 469	50.36 476	90.95 464	87.35 475	55.47 466	58.95 465	88.14 452	20.64 475	87.60 464	57.28 468	64.69 459	80.39 465

test_f		78.40 426	77.59 428	80.81 441	80.82 466	62.48 466	96.96 420	93.08 461	83.44 420	74.57 452	84.57 463	27.95 471	92.63 451	84.15 393	72.79 439	87.32 460

FE-MVS		95.70 210	95.01 220	97.79 181	98.21 204	94.57 240	95.03 444	98.69 81	88.90 352	97.50 185	96.19 342	92.60 146	99.49 183	89.99 335	97.94 190	99.31 211

FA-MVS(test-final)		95.86 200	95.09 216	98.15 156	97.74 235	95.62 197	96.31 432	98.17 218	91.42 290	96.26 229	96.13 346	90.56 189	99.47 186	92.18 293	97.07 219	99.35 202

balanced_conf03		98.27 63	97.99 70	99.11 77	98.64 169	98.43 67	99.47 257	97.79 261	94.56 140	99.74 42	98.35 268	94.33 91	99.25 193	99.12 77	99.96 46	99.64 135

MonoMVSNet		94.82 234	94.43 235	95.98 269	94.54 377	90.73 347	99.03 317	97.06 367	93.16 209	93.15 285	95.47 371	88.29 221	97.57 327	97.85 161	91.33 308	99.62 142

patch_mono-2		98.24 69	99.12 5	95.59 282	99.67 87	86.91 405	99.95 71	98.89 52	97.60 33	99.90 6	99.76 71	96.54 34	99.98 50	99.94 14	99.82 85	99.88 97

EGC-MVSNET		69.38 429	63.76 439	86.26 433	90.32 442	81.66 441	96.24 434	93.85 456	0.99 480	3.22 481	92.33 436	52.44 455	92.92 450	59.53 467	84.90 362	84.21 461

test2506		97.53 113	97.19 119	98.58 121	98.66 166	96.90 138	98.81 347	99.77 5	94.93 124	97.95 168	98.96 200	92.51 150	99.20 199	94.93 235	98.15 181	99.64 135

test1111		95.57 214	94.98 221	97.37 221	98.56 172	93.37 283	98.86 342	98.45 142	94.95 123	96.63 214	98.95 205	75.21 383	99.11 205	95.02 232	98.14 183	99.64 135

ECVR-MVS		95.66 211	95.05 218	97.51 210	98.66 166	93.71 270	98.85 344	98.45 142	94.93 124	96.86 208	98.96 200	75.22 382	99.20 199	95.34 225	98.15 181	99.64 135

test_blank		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.02 481	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

tt0805		91.28 332	90.18 340	94.60 317	96.26 332	87.55 397	98.39 379	98.72 77	89.00 346	89.22 345	98.47 263	62.98 437	98.96 217	90.57 324	88.00 337	97.28 308

DVP-MVS++		99.26 6	99.09 9	99.77 8	99.91 43	99.31 10	99.95 71	98.43 155	96.48 77	99.80 25	99.93 11	97.44 14	100.00 1	99.92 16	99.98 32	100.00 1

FOURS1					99.92 35	97.66 103	99.95 71	98.36 187	95.58 110	99.52 73

MSC_two_6792asdad				99.93 2	99.91 43	99.80 2		98.41 172					100.00 1	99.96 12	100.00 1	100.00 1

PC_three_1452									96.96 59	99.80 25	99.79 62	97.49 10	100.00 1	99.99 5	99.98 32	100.00 1

No_MVS				99.93 2	99.91 43	99.80 2		98.41 172					100.00 1	99.96 12	100.00 1	100.00 1

test_one_0601					99.94 16	99.30 12		98.41 172	96.63 72	99.75 39	99.93 11	97.49 10

eth-test2					0.00 486

eth-test					0.00 486

GeoE		94.36 259	93.48 267	96.99 236	97.29 283	93.54 276	99.96 52	96.72 400	88.35 365	93.43 280	98.94 207	82.05 306	98.05 307	88.12 358	96.48 236	99.37 196

test_method		80.79 420	79.70 423	84.08 436	92.83 412	67.06 462	99.51 249	95.42 433	54.34 468	81.07 427	93.53 423	44.48 463	92.22 454	78.90 428	77.23 423	92.94 414

Anonymous20240521		85.15 399	83.81 401	89.16 419	88.32 450	82.69 431	98.80 350	95.74 423	79.72 439	81.53 423	90.99 440	65.38 428	94.16 437	72.69 446	81.11 393	90.63 440

h-mvs33		94.92 233	94.36 237	96.59 251	98.85 153	91.29 337	98.93 332	98.94 44	95.90 98	98.77 126	98.42 266	90.89 184	99.77 148	97.80 163	70.76 443	98.72 266

hse-mvs2		94.38 256	94.08 247	95.31 294	98.27 200	90.02 364	99.29 286	98.56 112	95.90 98	98.77 126	98.00 284	90.89 184	98.26 295	97.80 163	69.20 449	97.64 298

CL-MVSNet_self_test		84.50 406	83.15 406	88.53 425	86.00 455	81.79 439	98.82 346	97.35 313	85.12 406	83.62 414	90.91 442	76.66 366	91.40 456	69.53 452	60.36 466	92.40 423

KD-MVS_2432*1600		88.00 385	86.10 389	93.70 357	96.91 307	94.04 261	97.17 414	97.12 352	84.93 408	81.96 419	92.41 433	92.48 151	94.51 435	79.23 424	52.68 469	92.56 419

KD-MVS_self_test		83.59 412	82.06 412	88.20 427	86.93 453	80.70 446	97.21 412	96.38 411	82.87 425	82.49 417	88.97 449	67.63 419	92.32 453	73.75 445	62.30 465	91.58 431

AUN-MVS		93.28 287	92.60 292	95.34 292	98.29 197	90.09 363	99.31 281	98.56 112	91.80 277	96.35 228	98.00 284	89.38 205	98.28 291	92.46 289	69.22 448	97.64 298

ZD-MVS					99.92 35	98.57 60		98.52 127	92.34 255	99.31 91	99.83 50	95.06 62	99.80 141	99.70 48	99.97 42

SR-MVS-dyc-post		98.31 60	98.17 57	98.71 107	99.79 68	96.37 163	99.76 178	98.31 198	94.43 149	99.40 85	99.75 79	93.28 124	99.78 145	98.90 96	99.92 68	99.97 66

RE-MVS-def			98.13 60		99.79 68	96.37 163	99.76 178	98.31 198	94.43 149	99.40 85	99.75 79	92.95 134		98.90 96	99.92 68	99.97 66

SED-MVS		99.28 5	99.11 7	99.77 8	99.93 27	99.30 12	99.96 52	98.43 155	97.27 46	99.80 25	99.94 4	96.71 29	100.00 1	100.00 1	100.00 1	100.00 1

IU-MVS					99.93 27	99.31 10		98.41 172	97.71 30	99.84 20				100.00 1	100.00 1	100.00 1

OPU-MVS				99.93 2	99.89 49	99.80 2	99.96 52				99.80 58	97.44 14	100.00 1	100.00 1	99.98 32	100.00 1

test_241102_TWO								98.43 155	97.27 46	99.80 25	99.94 4	97.18 23	100.00 1	100.00 1	100.00 1	100.00 1

test_241102_ONE					99.93 27	99.30 12		98.43 155	97.26 48	99.80 25	99.88 28	96.71 29	100.00 1

SF-MVS		98.67 33	98.40 39	99.50 34	99.77 71	98.67 53	99.90 113	98.21 213	93.53 192	99.81 23	99.89 26	94.70 76	99.86 127	99.84 28	99.93 65	99.96 74

cl22		93.77 275	93.25 279	95.33 293	99.49 101	94.43 246	99.61 227	98.09 230	90.38 322	89.16 349	95.61 361	90.56 189	97.34 335	91.93 300	84.45 366	94.21 352

miper_ehance_all_eth		93.16 291	92.60 292	94.82 310	97.57 256	93.56 275	99.50 251	97.07 366	88.75 356	88.85 353	95.52 367	90.97 180	96.74 378	90.77 321	84.45 366	94.17 354

miper_enhance_ethall		94.36 259	93.98 250	95.49 283	98.68 163	95.24 219	99.73 192	97.29 327	93.28 203	89.86 325	95.97 351	94.37 88	97.05 356	92.20 292	84.45 366	94.19 353

ZNCC-MVS		98.31 60	98.03 67	99.17 65	99.88 53	97.59 104	99.94 89	98.44 147	94.31 157	98.50 144	99.82 53	93.06 131	99.99 39	98.30 134	99.99 21	99.93 87

dcpmvs_2		97.42 120	98.09 63	95.42 289	99.58 95	87.24 401	99.23 292	96.95 380	94.28 160	98.93 117	99.73 90	94.39 87	99.16 204	99.89 21	99.82 85	99.86 101

cl____		92.31 312	91.58 313	94.52 322	97.33 279	92.77 293	99.57 237	96.78 397	86.97 385	87.56 375	95.51 368	89.43 204	96.62 383	88.60 348	82.44 381	94.16 359

DIV-MVS_self_test		92.32 311	91.60 312	94.47 326	97.31 281	92.74 295	99.58 234	96.75 398	86.99 384	87.64 373	95.54 365	89.55 203	96.50 388	88.58 349	82.44 381	94.17 354

eth_miper_zixun_eth		92.41 310	91.93 307	93.84 352	97.28 284	90.68 349	98.83 345	96.97 378	88.57 361	89.19 348	95.73 358	89.24 210	96.69 381	89.97 336	81.55 387	94.15 360

9.14			98.38 41		99.87 55		99.91 107	98.33 194	93.22 204	99.78 36	99.89 26	94.57 80	99.85 128	99.84 28	99.97 42

uanet_test		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

DCPMVS		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

save fliter					99.82 64	98.79 41	99.96 52	98.40 176	97.66 32

ET-MVSNet_ETH3D		94.37 257	93.28 278	97.64 194	98.30 196	97.99 84	99.99 5	97.61 284	94.35 154	71.57 456	99.45 139	96.23 38	95.34 423	96.91 197	85.14 360	99.59 149

UniMVSNet_ETH3D		90.06 362	88.58 371	94.49 325	94.67 375	88.09 394	97.81 402	97.57 289	83.91 417	88.44 361	97.41 301	57.44 449	97.62 326	91.41 307	88.59 329	97.77 295

EIA-MVS		97.53 113	97.46 103	97.76 187	98.04 217	94.84 232	99.98 20	97.61 284	94.41 152	97.90 170	99.59 123	92.40 154	98.87 223	98.04 150	99.13 145	99.59 149

miper_refine_blended		88.00 385	86.10 389	93.70 357	96.91 307	94.04 261	97.17 414	97.12 352	84.93 408	81.96 419	92.41 433	92.48 151	94.51 435	79.23 424	52.68 469	92.56 419

miper_lstm_enhance		91.81 320	91.39 319	93.06 374	97.34 277	89.18 377	99.38 271	96.79 396	86.70 388	87.47 377	95.22 387	90.00 197	95.86 414	88.26 354	81.37 389	94.15 360

ETV-MVS		97.92 83	97.80 87	98.25 149	98.14 211	96.48 156	99.98 20	97.63 278	95.61 109	99.29 94	99.46 138	92.55 148	98.82 227	99.02 87	98.54 168	99.46 180

CS-MVS		97.79 98	97.91 79	97.43 216	99.10 123	94.42 247	99.99 5	97.10 359	95.07 121	99.68 49	99.75 79	92.95 134	98.34 284	98.38 127	99.14 144	99.54 163

D2MVS		92.76 300	92.59 296	93.27 367	95.13 366	89.54 373	99.69 209	99.38 22	92.26 261	87.59 374	94.61 408	85.05 276	97.79 319	91.59 305	88.01 336	92.47 422

DVP-MVS		99.30 4	99.16 3	99.73 13	99.93 27	99.29 15	99.95 71	98.32 196	97.28 44	99.83 21	99.91 18	97.22 21	100.00 1	99.99 5	100.00 1	99.89 96
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									96.48 77	99.83 21	99.91 18	97.87 5	100.00 1	99.92 16	100.00 1	100.00 1

test_0728_SECOND				99.82 7	99.94 16	99.47 7	99.95 71	98.43 155					100.00 1	99.99 5	100.00 1	100.00 1

test0726					99.93 27	99.29 15	99.96 52	98.42 167	97.28 44	99.86 14	99.94 4	97.22 21

SR-MVS		98.46 47	98.30 50	98.93 95	99.88 53	97.04 132	99.84 148	98.35 189	94.92 126	99.32 90	99.80 58	93.35 119	99.78 145	99.30 71	99.95 54	99.96 74

DPM-MVS		98.83 24	98.46 36	99.97 1	99.33 108	99.92 1	99.96 52	98.44 147	97.96 22	99.55 68	99.94 4	97.18 23	100.00 1	93.81 267	99.94 59	99.98 56

GST-MVS		98.27 63	97.97 72	99.17 65	99.92 35	97.57 105	99.93 96	98.39 179	94.04 172	98.80 123	99.74 86	92.98 133	100.00 1	98.16 142	99.76 89	99.93 87

test_yl		97.83 91	97.37 110	99.21 59	99.18 117	97.98 85	99.64 220	99.27 27	91.43 288	97.88 173	98.99 194	95.84 45	99.84 136	98.82 100	95.32 272	99.79 111

thisisatest0530		97.10 135	96.72 142	98.22 150	97.60 254	96.70 144	99.92 99	98.54 122	91.11 299	97.07 200	98.97 198	97.47 12	99.03 210	93.73 272	96.09 244	98.92 253

Anonymous20240529		92.10 316	90.65 328	96.47 253	98.82 154	90.61 351	98.72 355	98.67 86	75.54 450	93.90 278	98.58 251	66.23 424	99.90 111	94.70 245	90.67 309	98.90 256

Anonymous202405211		93.10 293	91.99 306	96.40 258	99.10 123	89.65 371	98.88 338	97.93 246	83.71 418	94.00 276	98.75 230	68.79 411	99.88 122	95.08 231	91.71 305	99.68 127

DCV-MVSNet		97.83 91	97.37 110	99.21 59	99.18 117	97.98 85	99.64 220	99.27 27	91.43 288	97.88 173	98.99 194	95.84 45	99.84 136	98.82 100	95.32 272	99.79 111

tttt0517		96.85 149	96.49 151	97.92 171	97.48 265	95.89 183	99.85 143	98.54 122	90.72 316	96.63 214	98.93 210	97.47 12	99.02 211	93.03 285	95.76 256	98.85 257

our_test_3		90.39 351	89.48 356	93.12 371	92.40 420	89.57 372	99.33 278	96.35 413	87.84 372	85.30 402	94.99 397	84.14 292	96.09 408	80.38 419	84.56 365	93.71 397

thisisatest0515		97.41 121	97.02 127	98.59 120	97.71 242	97.52 107	99.97 38	98.54 122	91.83 274	97.45 186	99.04 188	97.50 9	99.10 207	94.75 243	96.37 239	99.16 229

ppachtmachnet_test		89.58 371	88.35 374	93.25 369	92.40 420	90.44 356	99.33 278	96.73 399	85.49 403	85.90 399	95.77 354	81.09 321	96.00 412	76.00 441	82.49 380	93.30 405

SMA-MVS		98.76 29	98.48 35	99.62 21	99.87 55	98.87 34	99.86 140	98.38 183	93.19 206	99.77 37	99.94 4	95.54 49	100.00 1	99.74 42	99.99 21	100.00 1
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																99.59 149

DPE-MVS		99.26 6	99.10 8	99.74 12	99.89 49	99.24 20	99.87 129	98.44 147	97.48 38	99.64 55	99.94 4	96.68 31	99.99 39	99.99 5	100.00 1	99.99 24
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2					99.89 49	99.25 19				99.49 76

thres100view900		96.74 158	95.92 183	99.18 62	98.90 149	98.77 46	99.74 185	99.71 7	92.59 242	95.84 241	98.86 221	89.25 208	99.50 178	93.84 264	94.57 281	99.27 220

tfpnnormal		89.29 375	87.61 382	94.34 333	94.35 381	94.13 259	98.95 329	98.94 44	83.94 415	84.47 408	95.51 368	74.84 385	97.39 332	77.05 437	80.41 401	91.48 432

tfpn200view9		96.79 152	95.99 171	99.19 61	98.94 139	98.82 38	99.78 167	99.71 7	92.86 223	96.02 237	98.87 219	89.33 206	99.50 178	93.84 264	94.57 281	99.27 220

c3_l		92.53 307	91.87 309	94.52 322	97.40 270	92.99 291	99.40 265	96.93 385	87.86 371	88.69 356	95.44 372	89.95 198	96.44 391	90.45 327	80.69 400	94.14 363

CHOSEN 280x420		99.01 17	99.03 10	98.95 94	99.38 106	98.87 34	98.46 372	99.42 21	97.03 56	99.02 113	99.09 181	99.35 2	98.21 297	99.73 44	99.78 88	99.77 115

CANet		98.27 63	97.82 86	99.63 18	99.72 81	99.10 24	99.98 20	98.51 130	97.00 58	98.52 141	99.71 96	87.80 226	99.95 84	99.75 40	99.38 132	99.83 104

Fast-Effi-MVS+-dtu		93.72 278	93.86 255	93.29 366	97.06 295	86.16 407	99.80 164	96.83 392	92.66 237	92.58 293	97.83 294	81.39 316	97.67 324	89.75 338	96.87 228	96.05 321

Effi-MVS+-dtu		94.53 249	95.30 207	92.22 386	97.77 233	82.54 433	99.59 232	97.06 367	94.92 126	95.29 256	95.37 378	85.81 260	97.89 316	94.80 241	97.07 219	96.23 318

CANet_DTU		96.76 155	96.15 166	98.60 117	98.78 157	97.53 106	99.84 148	97.63 278	97.25 49	99.20 98	99.64 117	81.36 317	99.98 50	92.77 288	98.89 154	98.28 281

MGCNet		99.06 14	98.84 20	99.72 14	99.76 72	99.21 22	99.99 5	99.34 25	98.70 2	99.44 79	99.75 79	93.24 126	99.99 39	99.94 14	99.41 130	99.95 82

MP-MVS-pluss		98.07 78	97.64 95	99.38 48	99.74 76	98.41 68	99.74 185	98.18 217	93.35 199	96.45 223	99.85 37	92.64 144	99.97 63	98.91 95	99.89 74	99.77 115
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS		99.09 10	99.12 5	98.98 91	99.93 27	97.24 120	99.95 71	98.42 167	97.50 37	99.52 73	99.88 28	97.43 16	99.71 158	99.50 60	99.98 32	100.00 1
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												94.72 74				99.59 149

sam_mvs												94.25 94

IterMVS-SCA-FT		90.85 342	90.16 342	92.93 376	96.72 321	89.96 366	98.89 336	96.99 374	88.95 350	86.63 387	95.67 359	76.48 369	95.00 427	87.04 371	84.04 372	93.84 388

TSAR-MVS + MP.		98.93 20	98.77 22	99.41 43	99.74 76	98.67 53	99.77 172	98.38 183	96.73 68	99.88 11	99.74 86	94.89 69	99.59 172	99.80 31	99.98 32	99.97 66
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		97.43 116	97.06 122	98.55 123	97.74 235	98.14 73	99.31 281	97.86 255	96.43 80	99.62 59	99.69 103	85.56 267	99.68 163	99.05 80	98.31 174	97.83 292

OPM-MVS		93.21 288	92.80 287	94.44 328	93.12 403	90.85 346	99.77 172	97.61 284	96.19 93	91.56 303	98.65 240	75.16 384	98.47 264	93.78 270	89.39 317	93.99 376
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP		98.49 45	98.14 59	99.54 31	99.66 88	98.62 59	99.85 143	98.37 186	94.68 137	99.53 71	99.83 50	92.87 136	100.00 1	98.66 112	99.84 80	99.99 24

ambc				83.23 438	77.17 471	62.61 464	87.38 468	94.55 450		76.72 446	86.65 459	30.16 467	96.36 395	84.85 392	69.86 444	90.73 438

MTGPA								98.28 203

SPE-MVS-test		97.88 85	97.94 77	97.70 190	99.28 111	95.20 222	99.98 20	97.15 347	95.53 112	99.62 59	99.79 62	92.08 162	98.38 280	98.75 106	99.28 138	99.52 169

Effi-MVS+		96.30 184	95.69 192	98.16 153	97.85 228	96.26 166	97.41 408	97.21 339	90.37 323	98.65 135	98.58 251	86.61 250	98.70 247	97.11 186	97.37 203	99.52 169

xiu_mvs_v2_base		98.23 71	97.97 72	99.02 87	98.69 162	98.66 55	99.52 247	98.08 232	97.05 55	99.86 14	99.86 33	90.65 186	99.71 158	99.39 69	98.63 164	98.69 267

xiu_mvs_v1_base		97.43 116	97.06 122	98.55 123	97.74 235	98.14 73	99.31 281	97.86 255	96.43 80	99.62 59	99.69 103	85.56 267	99.68 163	99.05 80	98.31 174	97.83 292

new-patchmatchnet		81.19 417	79.34 424	86.76 432	82.86 462	80.36 449	97.92 398	95.27 437	82.09 430	72.02 455	86.87 458	62.81 438	90.74 459	71.10 449	63.08 462	89.19 455

pmmvs6		85.69 393	83.84 400	91.26 397	90.00 445	84.41 420	97.82 401	96.15 417	75.86 448	81.29 425	95.39 376	61.21 443	96.87 372	83.52 401	73.29 437	92.50 421

pmmvs5		90.17 360	89.09 361	93.40 363	92.10 425	89.77 370	99.74 185	95.58 430	85.88 397	87.24 382	95.74 355	73.41 395	96.48 389	88.54 350	83.56 374	93.95 379

test_post1							95.78 442				59.23 478	93.20 128	97.74 322	91.06 313

test_post											63.35 475	94.43 82	98.13 301

Fast-Effi-MVS+		95.02 230	94.19 242	97.52 209	97.88 225	94.55 241	99.97 38	97.08 363	88.85 354	94.47 266	97.96 288	84.59 285	98.41 272	89.84 337	97.10 218	99.59 149

patchmatchnet-post											91.70 438	95.12 59	97.95 313

Anonymous20231211		89.86 365	88.44 373	94.13 339	98.93 141	90.68 349	98.54 369	98.26 206	76.28 446	86.73 385	95.54 365	70.60 407	97.56 328	90.82 320	80.27 404	94.15 360

pmmvs-eth3d		84.03 409	81.97 413	90.20 411	84.15 459	87.09 402	98.10 394	94.73 446	83.05 423	74.10 454	87.77 455	65.56 427	94.01 438	81.08 415	69.24 447	89.49 452

GG-mvs-BLEND				98.54 127	98.21 204	98.01 83	93.87 449	98.52 127		97.92 169	97.92 289	99.02 3	97.94 315	98.17 141	99.58 108	99.67 129

xiu_mvs_v1_base_debi		97.43 116	97.06 122	98.55 123	97.74 235	98.14 73	99.31 281	97.86 255	96.43 80	99.62 59	99.69 103	85.56 267	99.68 163	99.05 80	98.31 174	97.83 292

Anonymous20231206		86.32 391	85.42 394	89.02 420	89.11 449	80.53 448	99.05 314	95.28 436	85.43 404	82.82 416	93.92 418	74.40 388	93.44 446	66.99 456	81.83 386	93.08 411

MTAPA		98.29 62	97.96 75	99.30 51	99.85 60	97.93 89	99.39 269	98.28 203	95.76 104	97.18 197	99.88 28	92.74 140	100.00 1	98.67 110	99.88 77	99.99 24

MTMP							99.87 129	96.49 409

gm-plane-assit					96.97 300	93.76 269			91.47 286		98.96 200		98.79 232	94.92 236

test9_res														99.71 47	99.99 21	100.00 1

MVP-Stereo		90.93 338	90.45 333	92.37 385	91.25 436	88.76 382	98.05 396	96.17 416	87.27 379	84.04 409	95.30 381	78.46 352	97.27 345	83.78 398	99.70 93	91.09 433
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9					99.92 35	98.92 30	99.96 52	98.43 155	93.90 180	99.71 46	99.86 33	95.88 44	99.85 128

train_agg		98.88 23	98.65 27	99.59 26	99.92 35	98.92 30	99.96 52	98.43 155	94.35 154	99.71 46	99.86 33	95.94 41	99.85 128	99.69 49	99.98 32	99.99 24

gg-mvs-nofinetune		93.51 283	91.86 310	98.47 134	97.72 240	97.96 88	92.62 455	98.51 130	74.70 453	97.33 191	69.59 470	98.91 4	97.79 319	97.77 168	99.56 109	99.67 129

SCA		94.69 242	93.81 256	97.33 226	97.10 291	94.44 245	98.86 342	98.32 196	93.30 202	96.17 234	95.59 363	76.48 369	97.95 313	91.06 313	97.43 199	99.59 149

Patchmatch-test		92.65 305	91.50 316	96.10 267	96.85 312	90.49 354	91.50 460	97.19 340	82.76 427	90.23 317	95.59 363	95.02 64	98.00 309	77.41 434	96.98 226	99.82 106

test_8					99.92 35	98.88 33	99.96 52	98.43 155	94.35 154	99.69 48	99.85 37	95.94 41	99.85 128

MS-PatchMatch		90.65 345	90.30 336	91.71 394	94.22 384	85.50 413	98.24 385	97.70 270	88.67 358	86.42 392	96.37 337	67.82 418	98.03 308	83.62 399	99.62 99	91.60 430

Patchmatch-RL test		86.90 389	85.98 393	89.67 415	84.45 458	75.59 454	89.71 466	92.43 462	86.89 386	77.83 442	90.94 441	94.22 95	93.63 444	87.75 361	69.61 445	99.79 111

cdsmvs_eth3d_5k		23.43 445	31.24 448	0.00 463	0.00 486	0.00 488	0.00 475	98.09 230	0.00 481	0.00 482	99.67 112	83.37 297	0.00 482	0.00 481	0.00 480	0.00 478

pcd_1.5k_mvsjas		7.60 448	10.13 451	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	91.20 173	0.00 482	0.00 481	0.00 480	0.00 478

agg_prior2														99.48 62	100.00 1	100.00 1

agg_prior					99.93 27	98.77 46		98.43 155		99.63 56			99.85 128

tmp_tt		65.23 437	62.94 440	72.13 453	44.90 482	50.03 478	81.05 470	89.42 473	38.45 472	48.51 474	99.90 22	54.09 453	78.70 474	91.84 303	18.26 476	87.64 458

canonicalmvs		97.09 137	96.32 158	99.39 45	98.93 141	98.95 28	99.72 196	97.35 313	94.45 145	97.88 173	99.42 140	86.71 246	99.52 174	98.48 122	93.97 291	99.72 121

anonymousdsp		91.79 325	90.92 325	94.41 331	90.76 439	92.93 292	98.93 332	97.17 344	89.08 342	87.46 378	95.30 381	78.43 353	96.92 367	92.38 290	88.73 325	93.39 403

alignmvs		97.81 95	97.33 112	99.25 55	98.77 158	98.66 55	99.99 5	98.44 147	94.40 153	98.41 149	99.47 136	93.65 113	99.42 188	98.57 116	94.26 287	99.67 129

nrg030		93.51 283	92.53 297	96.45 256	94.36 380	97.20 122	99.81 160	97.16 346	91.60 280	89.86 325	97.46 299	86.37 252	97.68 323	95.88 218	80.31 403	94.46 329

v144192		90.79 343	89.52 353	94.59 318	93.11 404	92.77 293	99.56 240	96.99 374	86.38 391	89.82 328	94.95 399	80.50 331	97.10 353	83.98 396	80.41 401	93.90 383

FIs		94.10 264	93.43 268	96.11 266	94.70 374	96.82 140	99.58 234	98.93 48	92.54 245	89.34 341	97.31 304	87.62 229	97.10 353	94.22 257	86.58 349	94.40 335

v1921920		90.46 350	89.12 360	94.50 324	92.96 408	92.46 305	99.49 253	96.98 376	86.10 394	89.61 335	95.30 381	78.55 351	97.03 361	82.17 409	80.89 399	94.01 373

UA-Net		96.54 169	95.96 177	98.27 148	98.23 202	95.71 191	98.00 397	98.45 142	93.72 188	98.41 149	99.27 160	88.71 219	99.66 169	91.19 310	97.69 193	99.44 188

v1192		90.62 348	89.25 358	94.72 313	93.13 401	93.07 286	99.50 251	97.02 371	86.33 392	89.56 337	95.01 394	79.22 342	97.09 355	82.34 408	81.16 391	94.01 373

FC-MVSNet-test		93.81 273	93.15 281	95.80 278	94.30 382	96.20 172	99.42 264	98.89 52	92.33 256	89.03 351	97.27 306	87.39 235	96.83 375	93.20 279	86.48 350	94.36 337

v1144		91.09 336	89.83 345	94.87 306	93.25 400	93.69 272	99.62 223	96.98 376	86.83 387	89.64 333	94.99 397	80.94 322	97.05 356	85.08 389	81.16 391	93.87 386

sosnet-low-res		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

HFP-MVS		98.56 39	98.37 43	99.14 72	99.96 8	97.43 113	99.95 71	98.61 98	94.77 132	99.31 91	99.85 37	94.22 95	100.00 1	98.70 108	99.98 32	99.98 56

v148		90.70 344	89.63 349	93.92 348	92.97 407	90.97 340	99.75 182	96.89 388	87.51 374	88.27 366	95.01 394	81.67 312	97.04 359	87.40 365	77.17 424	93.75 392

sosnet		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

uncertanet		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

AllTest		92.48 308	91.64 311	95.00 302	99.01 129	88.43 389	98.94 330	96.82 394	86.50 389	88.71 354	98.47 263	74.73 386	99.88 122	85.39 385	96.18 242	96.71 312

TestCases				95.00 302	99.01 129	88.43 389		96.82 394	86.50 389	88.71 354	98.47 263	74.73 386	99.88 122	85.39 385	96.18 242	96.71 312

v7n		89.65 369	88.29 375	93.72 354	92.22 422	90.56 353	99.07 309	97.10 359	85.42 405	86.73 385	94.72 402	80.06 335	97.13 350	81.14 414	78.12 415	93.49 400

region2R		98.54 41	98.37 43	99.05 82	99.96 8	97.18 123	99.96 52	98.55 118	94.87 129	99.45 78	99.85 37	94.07 101	100.00 1	98.67 110	100.00 1	99.98 56

RRT-MVS		96.24 188	95.68 194	97.94 170	97.65 249	94.92 230	99.27 289	97.10 359	92.79 229	97.43 187	97.99 286	81.85 310	99.37 190	98.46 124	98.57 165	99.53 167

mamv4		95.24 223	96.90 130	90.25 410	98.65 168	72.11 458	98.28 383	97.64 277	89.99 333	95.93 239	98.25 276	94.74 73	99.11 205	99.01 88	99.64 96	99.53 167

PS-MVSNAJss		93.64 280	93.31 277	94.61 316	92.11 424	92.19 310	99.12 299	97.38 309	92.51 248	88.45 360	96.99 317	91.20 173	97.29 343	94.36 251	87.71 340	94.36 337

PS-MVSNAJ		98.44 49	98.20 54	99.16 68	98.80 156	98.92 30	99.54 245	98.17 218	97.34 41	99.85 17	99.85 37	91.20 173	99.89 116	99.41 67	99.67 94	98.69 267

jajsoiax		91.92 318	91.18 321	94.15 337	91.35 434	90.95 343	99.00 320	97.42 305	92.61 240	87.38 379	97.08 311	72.46 397	97.36 333	94.53 249	88.77 324	94.13 365

mvs_tets		91.81 320	91.08 323	94.00 345	91.63 431	90.58 352	98.67 361	97.43 303	92.43 250	87.37 380	97.05 314	71.76 399	97.32 338	94.75 243	88.68 326	94.11 366

EI-MVSNet-UG-set		98.14 74	97.99 70	98.60 117	99.80 67	96.27 165	99.36 275	98.50 136	95.21 120	98.30 155	99.75 79	93.29 123	99.73 157	98.37 129	99.30 137	99.81 108

EI-MVSNet-Vis-set		98.27 63	98.11 62	98.75 105	99.83 63	96.59 154	99.40 265	98.51 130	95.29 118	98.51 143	99.76 71	93.60 115	99.71 158	98.53 120	99.52 113	99.95 82

HPM-MVS++		99.07 12	98.88 18	99.63 18	99.90 46	99.02 26	99.95 71	98.56 112	97.56 36	99.44 79	99.85 37	95.38 55	100.00 1	99.31 70	99.99 21	99.87 99

test_prior4						98.05 81	99.94 89

XVS		98.70 32	98.55 31	99.15 70	99.94 16	97.50 109	99.94 89	98.42 167	96.22 91	99.41 83	99.78 66	94.34 89	99.96 75	98.92 93	99.95 54	99.99 24

v1240		90.20 358	88.79 367	94.44 328	93.05 406	92.27 309	99.38 271	96.92 386	85.89 396	89.36 340	94.87 401	77.89 354	97.03 361	80.66 417	81.08 394	94.01 373

pm-mvs1		89.36 374	87.81 380	94.01 344	93.40 399	91.93 316	98.62 365	96.48 410	86.25 393	83.86 412	96.14 345	73.68 392	97.04 359	86.16 380	75.73 432	93.04 412

test_prior2							99.95 71		95.78 103	99.73 44	99.76 71	96.00 40		99.78 34	100.00 1

X-MVStestdata		93.83 270	92.06 305	99.15 70	99.94 16	97.50 109	99.94 89	98.42 167	96.22 91	99.41 83	41.37 479	94.34 89	99.96 75	98.92 93	99.95 54	99.99 24

test_prior				99.43 40	99.94 16	98.49 65		98.65 87					99.80 141			99.99 24

旧先验2							99.46 261		94.21 163	99.85 17			99.95 84	96.96 194

新几何2							99.40 265

新几何1				99.42 42	99.75 75	98.27 70		98.63 96	92.69 235	99.55 68	99.82 53	94.40 84	100.00 1	91.21 309	99.94 59	99.99 24

旧先验1					99.76 72	97.52 107		98.64 90			99.85 37	95.63 48			99.94 59	99.99 24

无先验							99.49 253	98.71 78	93.46 195				100.00 1	94.36 251		99.99 24

原ACMM2							99.90 113

原ACMM1				98.96 93	99.73 79	96.99 134		98.51 130	94.06 170	99.62 59	99.85 37	94.97 68	99.96 75	95.11 230	99.95 54	99.92 92

test222					99.55 96	97.41 115	99.34 277	98.55 118	91.86 273	99.27 96	99.83 50	93.84 109			99.95 54	99.99 24

testdata2													99.99 39	90.54 326

segment_acmp												96.68 31

testdata				98.42 140	99.47 102	95.33 212		98.56 112	93.78 184	99.79 34	99.85 37	93.64 114	99.94 92	94.97 234	99.94 59	100.00 1

testdata1							99.28 287		96.35 89

v8		90.54 349	89.17 359	94.66 314	93.43 397	93.40 282	99.20 294	96.94 384	85.76 398	87.56 375	94.51 409	81.96 309	97.19 346	84.94 390	78.25 413	93.38 404

1314		96.84 150	95.96 177	99.48 39	96.74 320	98.52 62	98.31 381	98.86 59	95.82 102	89.91 323	98.98 196	87.49 233	99.96 75	97.80 163	99.73 91	99.96 74

LFMVS		94.75 241	93.56 264	98.30 146	99.03 128	95.70 192	98.74 353	97.98 241	87.81 373	98.47 145	99.39 147	67.43 420	99.53 173	98.01 151	95.20 275	99.67 129

VDD-MVS		93.77 275	92.94 284	96.27 263	98.55 175	90.22 360	98.77 352	97.79 261	90.85 306	96.82 210	99.42 140	61.18 444	99.77 148	98.95 89	94.13 288	98.82 259

VDDNet		93.12 292	91.91 308	96.76 245	96.67 325	92.65 301	98.69 359	98.21 213	82.81 426	97.75 180	99.28 157	61.57 442	99.48 184	98.09 147	94.09 289	98.15 283

v10		90.25 357	88.82 366	94.57 320	93.53 395	93.43 279	99.08 305	96.87 390	85.00 407	87.34 381	94.51 409	80.93 323	97.02 363	82.85 404	79.23 408	93.26 406

VPNet		91.81 320	90.46 331	95.85 275	94.74 373	95.54 200	98.98 322	98.59 102	92.14 263	90.77 314	97.44 300	68.73 413	97.54 329	94.89 239	77.89 416	94.46 329

MVS		96.60 165	95.56 197	99.72 14	96.85 312	99.22 21	98.31 381	98.94 44	91.57 281	90.90 310	99.61 122	86.66 249	99.96 75	97.36 177	99.88 77	99.99 24

v2v482		91.30 330	90.07 344	95.01 301	93.13 401	93.79 267	99.77 172	97.02 371	88.05 368	89.25 343	95.37 378	80.73 326	97.15 348	87.28 367	80.04 406	94.09 367

V42		91.28 332	90.12 343	94.74 311	93.42 398	93.46 278	99.68 212	97.02 371	87.36 377	89.85 327	95.05 392	81.31 319	97.34 335	87.34 366	80.07 405	93.40 402

SD-MVS		98.92 21	98.70 23	99.56 29	99.70 84	98.73 50	99.94 89	98.34 193	96.38 83	99.81 23	99.76 71	94.59 77	99.98 50	99.84 28	99.96 46	99.97 66
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		93.83 270	92.84 285	96.80 243	95.73 351	93.57 274	99.88 126	97.24 335	92.57 244	92.92 288	96.66 327	78.73 348	97.67 324	87.75 361	94.06 290	99.17 228

MSLP-MVS++		99.13 9	99.01 11	99.49 36	99.94 16	98.46 66	99.98 20	98.86 59	97.10 52	99.80 25	99.94 4	95.92 43	100.00 1	99.51 58	100.00 1	100.00 1

APDe-MVS		99.06 14	98.91 15	99.51 33	99.94 16	98.76 49	99.91 107	98.39 179	97.20 50	99.46 77	99.85 37	95.53 51	99.79 143	99.86 26	100.00 1	99.99 24
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize		98.25 68	98.08 64	98.78 102	99.81 66	96.60 152	99.82 158	98.30 201	93.95 176	99.37 88	99.77 69	92.84 137	99.76 151	98.95 89	99.92 68	99.97 66

ADS-MVSNet2		93.80 274	93.88 254	93.55 361	97.87 226	85.94 410	94.24 445	96.84 391	90.07 330	96.43 224	94.48 411	90.29 195	95.37 422	87.44 363	97.23 209	99.36 198

EI-MVSNet		93.73 277	93.40 272	94.74 311	96.80 315	92.69 298	99.06 310	97.67 273	88.96 349	91.39 304	99.02 189	88.75 218	97.30 340	91.07 312	87.85 338	94.22 350

Regformer		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

CVMVSNet		94.68 244	94.94 223	93.89 351	96.80 315	86.92 404	99.06 310	98.98 41	94.45 145	94.23 274	99.02 189	85.60 265	95.31 424	90.91 318	95.39 270	99.43 189

pmmvs4		92.10 316	91.07 324	95.18 297	92.82 413	94.96 228	99.48 256	96.83 392	87.45 376	88.66 357	96.56 333	83.78 294	96.83 375	89.29 342	84.77 364	93.75 392

EU-MVSNet		90.14 361	90.34 335	89.54 416	92.55 417	81.06 444	98.69 359	98.04 236	91.41 291	86.59 388	96.84 324	80.83 325	93.31 447	86.20 379	81.91 385	94.26 345

VNet		97.21 130	96.57 149	99.13 76	98.97 137	97.82 94	99.03 317	99.21 32	94.31 157	99.18 101	98.88 212	86.26 255	99.89 116	98.93 91	94.32 285	99.69 126

test-LLR		96.47 171	96.04 169	97.78 183	97.02 297	95.44 203	99.96 52	98.21 213	94.07 168	95.55 250	96.38 335	93.90 106	98.27 293	90.42 328	98.83 158	99.64 135

TESTMET0.1,1		96.74 158	96.26 160	98.16 153	97.36 276	96.48 156	99.96 52	98.29 202	91.93 270	95.77 244	98.07 282	95.54 49	98.29 289	90.55 325	98.89 154	99.70 124

test-mter		96.39 177	95.93 182	97.78 183	97.02 297	95.44 203	99.96 52	98.21 213	91.81 276	95.55 250	96.38 335	95.17 58	98.27 293	90.42 328	98.83 158	99.64 135

VPA-MVSNet		92.70 302	91.55 315	96.16 265	95.09 367	96.20 172	98.88 338	99.00 39	91.02 303	91.82 301	95.29 384	76.05 375	97.96 312	95.62 224	81.19 390	94.30 343

ACMMPR		98.50 44	98.32 47	99.05 82	99.96 8	97.18 123	99.95 71	98.60 100	94.77 132	99.31 91	99.84 48	93.73 111	100.00 1	98.70 108	99.98 32	99.98 56

testgi		89.01 377	88.04 378	91.90 390	93.49 396	84.89 417	99.73 192	95.66 428	93.89 182	85.14 403	98.17 278	59.68 446	94.66 434	77.73 433	88.88 321	96.16 320

test20.03		84.72 405	83.99 397	86.91 431	88.19 452	80.62 447	98.88 338	95.94 420	88.36 364	78.87 435	94.62 407	68.75 412	89.11 462	66.52 458	75.82 430	91.00 435

thres600view7		96.69 161	95.87 186	99.14 72	98.90 149	98.78 45	99.74 185	99.71 7	92.59 242	95.84 241	98.86 221	89.25 208	99.50 178	93.44 277	94.50 284	99.16 229

ADS-MVSNet		94.79 237	94.02 249	97.11 232	97.87 226	93.79 267	94.24 445	98.16 223	90.07 330	96.43 224	94.48 411	90.29 195	98.19 298	87.44 363	97.23 209	99.36 198

MP-MVS		98.23 71	97.97 72	99.03 84	99.94 16	97.17 126	99.95 71	98.39 179	94.70 136	98.26 158	99.81 57	91.84 167	100.00 1	98.85 99	99.97 42	99.93 87
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs		40.60 443	44.45 446	29.05 461	19.49 485	14.11 487	99.68 212	18.47 484	20.74 477	64.59 462	98.48 262	10.95 481	17.09 481	56.66 470	11.01 477	55.94 474

thres400		96.78 154	95.99 171	99.16 68	98.94 139	98.82 38	99.78 167	99.71 7	92.86 223	96.02 237	98.87 219	89.33 206	99.50 178	93.84 264	94.57 281	99.16 229

test123		37.68 444	39.14 447	33.31 460	19.94 484	24.83 486	98.36 380	9.75 485	15.53 478	51.31 472	87.14 457	19.62 478	17.74 480	47.10 472	3.47 479	57.36 473

thres200		96.96 144	96.21 164	99.22 58	98.97 137	98.84 37	99.85 143	99.71 7	93.17 208	96.26 229	98.88 212	89.87 199	99.51 176	94.26 255	94.91 277	99.31 211

test0.0.03 1		93.86 269	93.61 259	94.64 315	95.02 370	92.18 311	99.93 96	98.58 104	94.07 168	87.96 369	98.50 258	93.90 106	94.96 428	81.33 413	93.17 300	96.78 311

pmmvs3		80.27 422	77.77 427	87.76 430	80.32 468	82.43 434	98.23 387	91.97 464	72.74 457	78.75 436	87.97 454	57.30 450	90.99 458	70.31 450	62.37 464	89.87 447

EMVS		51.44 442	51.22 444	52.11 459	70.71 475	44.97 482	94.04 447	75.66 481	35.34 476	42.40 476	61.56 477	28.93 469	65.87 478	27.64 479	24.73 474	45.49 475

E-PMN		52.30 440	52.18 442	52.67 458	71.51 474	45.40 480	93.62 451	76.60 480	36.01 474	43.50 475	64.13 474	27.11 472	67.31 477	31.06 478	26.06 473	45.30 476

PGM-MVS		98.34 58	98.13 60	98.99 89	99.92 35	97.00 133	99.75 182	99.50 17	93.90 180	99.37 88	99.76 71	93.24 126	100.00 1	97.75 170	99.96 46	99.98 56

LCM-MVSNet-Re		92.31 312	92.60 292	91.43 395	97.53 260	79.27 450	99.02 319	91.83 465	92.07 265	80.31 429	94.38 414	83.50 296	95.48 419	97.22 184	97.58 197	99.54 163

LCM-MVSNet		67.77 434	64.73 437	76.87 445	62.95 479	56.25 472	89.37 467	93.74 457	44.53 471	61.99 463	80.74 465	20.42 477	86.53 468	69.37 453	59.50 468	87.84 457

MCST-MVS		99.32 3	99.14 4	99.86 5	99.97 3	99.59 5	99.97 38	98.64 90	98.47 3	99.13 103	99.92 17	96.38 36	100.00 1	99.74 42	100.00 1	100.00 1

mvs_anonymous		95.65 212	95.03 219	97.53 207	98.19 206	95.74 189	99.33 278	97.49 299	90.87 305	90.47 316	97.10 310	88.23 222	97.16 347	95.92 217	97.66 196	99.68 127

MVS_Test		96.46 172	95.74 190	98.61 116	98.18 207	97.23 121	99.31 281	97.15 347	91.07 301	98.84 120	97.05 314	88.17 223	98.97 215	94.39 250	97.50 198	99.61 146

MDA-MVSNet-bldmvs		84.09 408	81.52 415	91.81 392	91.32 435	88.00 396	98.67 361	95.92 421	80.22 438	55.60 470	93.32 425	68.29 416	93.60 445	73.76 444	76.61 428	93.82 390

CDPH-MVS		98.65 35	98.36 45	99.49 36	99.94 16	98.73 50	99.87 129	98.33 194	93.97 174	99.76 38	99.87 31	94.99 67	99.75 152	98.55 117	100.00 1	99.98 56

test12				99.43 40	99.74 76	98.56 61		98.40 176		99.65 52		94.76 72	99.75 152		99.98 32	99.99 24

casdiffmvs		96.42 176	95.97 176	97.77 185	97.30 282	94.98 227	99.84 148	97.09 362	93.75 187	96.58 217	99.26 164	85.07 275	98.78 234	97.77 168	97.04 221	99.54 163
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		97.00 142	96.64 145	98.09 160	97.64 250	96.17 175	99.81 160	97.19 340	94.67 138	98.95 115	99.28 157	86.43 251	98.76 237	98.37 129	97.42 201	99.33 205
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		96.71 160	96.49 151	97.37 221	95.63 360	95.96 181	99.74 185	98.88 54	92.94 219	91.61 302	98.97 198	97.72 6	98.62 257	94.83 240	98.08 187	97.53 305

baseline1		95.78 204	94.86 224	98.54 127	98.47 185	98.07 79	99.06 310	97.99 239	92.68 236	94.13 275	98.62 245	93.28 124	98.69 248	93.79 269	85.76 353	98.84 258

YYNet1		85.50 397	83.33 403	92.00 388	90.89 438	88.38 392	99.22 293	96.55 407	79.60 441	57.26 468	92.72 429	79.09 346	93.78 443	77.25 435	77.37 422	93.84 388

PMMVS2		67.15 435	64.15 438	76.14 446	70.56 476	62.07 467	93.89 448	87.52 474	58.09 465	60.02 464	78.32 466	22.38 474	84.54 469	59.56 466	47.03 471	81.80 464

MDA-MVSNet_test_wron		85.51 396	83.32 404	92.10 387	90.96 437	88.58 388	99.20 294	96.52 408	79.70 440	57.12 469	92.69 430	79.11 344	93.86 441	77.10 436	77.46 421	93.86 387

tpmvs		94.28 261	93.57 263	96.40 258	98.55 175	91.50 335	95.70 443	98.55 118	87.47 375	92.15 297	94.26 416	91.42 169	98.95 218	88.15 356	95.85 253	98.76 262

PM-MVS		80.47 421	78.88 425	85.26 434	83.79 461	72.22 457	95.89 441	91.08 467	85.71 401	76.56 447	88.30 451	36.64 466	93.90 440	82.39 407	69.57 446	89.66 451

HQP_MVS		94.49 253	94.36 237	94.87 306	95.71 354	91.74 322	99.84 148	97.87 253	96.38 83	93.01 286	98.59 248	80.47 332	98.37 282	97.79 166	89.55 314	94.52 326

plane_prior7					95.71 354	91.59 334

plane_prior6					95.76 348	91.72 325						80.47 332

plane_prior5								97.87 253					98.37 282	97.79 166	89.55 314	94.52 326

plane_prior4											98.59 248

plane_prior3						91.64 328			96.63 72	93.01 286

plane_prior2							99.84 148		96.38 83

plane_prior1					95.73 351

plane_prior						91.74 322	99.86 140		96.76 67						89.59 313

PS-CasMVS		90.63 347	89.51 354	93.99 346	93.83 390	91.70 326	98.98 322	98.52 127	88.48 362	86.15 396	96.53 334	75.46 378	96.31 398	88.83 346	78.86 411	93.95 379

UniMVSNet_NR-MVSNet		92.95 296	92.11 303	95.49 283	94.61 376	95.28 217	99.83 155	99.08 36	91.49 283	89.21 346	96.86 321	87.14 239	96.73 379	93.20 279	77.52 419	94.46 329

PEN-MVS		90.19 359	89.06 362	93.57 360	93.06 405	90.90 344	99.06 310	98.47 139	88.11 367	85.91 398	96.30 339	76.67 365	95.94 413	87.07 370	76.91 426	93.89 384

TransMVSNet (Re)		87.25 388	85.28 395	93.16 370	93.56 394	91.03 339	98.54 369	94.05 454	83.69 419	81.09 426	96.16 343	75.32 379	96.40 393	76.69 438	68.41 451	92.06 426

DTE-MVSNet		89.40 373	88.24 376	92.88 377	92.66 416	89.95 367	99.10 302	98.22 212	87.29 378	85.12 404	96.22 341	76.27 372	95.30 425	83.56 400	75.74 431	93.41 401

DU-MVS		92.46 309	91.45 318	95.49 283	94.05 386	95.28 217	99.81 160	98.74 76	92.25 262	89.21 346	96.64 329	81.66 313	96.73 379	93.20 279	77.52 419	94.46 329

UniMVSNet (Re)		93.07 294	92.13 302	95.88 273	94.84 371	96.24 171	99.88 126	98.98 41	92.49 249	89.25 343	95.40 374	87.09 240	97.14 349	93.13 283	78.16 414	94.26 345

CP-MVSNet		91.23 334	90.22 338	94.26 335	93.96 388	92.39 307	99.09 303	98.57 106	88.95 350	86.42 392	96.57 332	79.19 343	96.37 394	90.29 331	78.95 409	94.02 371

WR-MVS_H		91.30 330	90.35 334	94.15 337	94.17 385	92.62 302	99.17 297	98.94 44	88.87 353	86.48 391	94.46 413	84.36 289	96.61 384	88.19 355	78.51 412	93.21 408

WR-MVS		92.31 312	91.25 320	95.48 286	94.45 379	95.29 216	99.60 230	98.68 83	90.10 329	88.07 368	96.89 319	80.68 327	96.80 377	93.14 282	79.67 407	94.36 337

NR-MVSNet		91.56 328	90.22 338	95.60 281	94.05 386	95.76 188	98.25 384	98.70 79	91.16 297	80.78 428	96.64 329	83.23 299	96.57 385	91.41 307	77.73 418	94.46 329

Baseline_NR-MVSNet		90.33 354	89.51 354	92.81 379	92.84 411	89.95 367	99.77 172	93.94 455	84.69 412	89.04 350	95.66 360	81.66 313	96.52 387	90.99 315	76.98 425	91.97 428

TranMVSNet+NR-MVSNet		91.68 327	90.61 330	94.87 306	93.69 393	93.98 264	99.69 209	98.65 87	91.03 302	88.44 361	96.83 325	80.05 336	96.18 403	90.26 332	76.89 427	94.45 334

TSAR-MVS + GP.		98.60 37	98.51 34	98.86 98	99.73 79	96.63 149	99.97 38	97.92 249	98.07 18	98.76 129	99.55 130	95.00 66	99.94 92	99.91 19	97.68 195	99.99 24

n2								0.00 487

nn								0.00 487

mPP-MVS		98.39 56	98.20 54	98.97 92	99.97 3	96.92 137	99.95 71	98.38 183	95.04 122	98.61 137	99.80 58	93.39 117	100.00 1	98.64 113	100.00 1	99.98 56

door-mid								89.69 471

XVG-OURS-SEG-HR		94.79 237	94.70 232	95.08 299	98.05 216	89.19 375	99.08 305	97.54 292	93.66 189	94.87 261	99.58 126	78.78 347	99.79 143	97.31 178	93.40 298	96.25 316

mvsmamba		96.94 145	96.73 141	97.55 205	97.99 219	94.37 252	99.62 223	97.70 270	93.13 211	98.42 148	97.92 289	88.02 224	98.75 239	98.78 103	99.01 151	99.52 169

MVSFormer		96.94 145	96.60 147	97.95 167	97.28 284	97.70 100	99.55 243	97.27 329	91.17 295	99.43 81	99.54 132	90.92 181	96.89 369	94.67 246	99.62 99	99.25 222

jason		97.24 128	96.86 133	98.38 143	95.73 351	97.32 116	99.97 38	97.40 308	95.34 117	98.60 140	99.54 132	87.70 227	98.56 260	97.94 156	99.47 123	99.25 222
jason: jason.
lupinMVS		97.85 89	97.60 97	98.62 115	97.28 284	97.70 100	99.99 5	97.55 290	95.50 114	99.43 81	99.67 112	90.92 181	98.71 244	98.40 126	99.62 99	99.45 185

test_djsdf		92.83 299	92.29 301	94.47 326	91.90 427	92.46 305	99.55 243	97.27 329	91.17 295	89.96 321	96.07 349	81.10 320	96.89 369	94.67 246	88.91 320	94.05 370

HPM-MVS_fast		97.80 96	97.50 102	98.68 109	99.79 68	96.42 158	99.88 126	98.16 223	91.75 278	98.94 116	99.54 132	91.82 168	99.65 170	97.62 173	99.99 21	99.99 24

K. test v3		88.05 384	87.24 385	90.47 407	91.82 429	82.23 436	98.96 328	97.42 305	89.05 343	76.93 445	95.60 362	68.49 414	95.42 421	85.87 384	81.01 397	93.75 392

lessismore_v0				90.53 405	90.58 440	80.90 445		95.80 422		77.01 444	95.84 352	66.15 425	96.95 365	83.03 403	75.05 434	93.74 395

SixPastTwentyTwo		88.73 378	88.01 379	90.88 398	91.85 428	82.24 435	98.22 389	95.18 440	88.97 348	82.26 418	96.89 319	71.75 400	96.67 382	84.00 395	82.98 375	93.72 396

OurMVSNet-221017-0		89.81 366	89.48 356	90.83 401	91.64 430	81.21 442	98.17 391	95.38 435	91.48 285	85.65 400	97.31 304	72.66 396	97.29 343	88.15 356	84.83 363	93.97 378

HPM-MVS		97.96 79	97.72 89	98.68 109	99.84 62	96.39 162	99.90 113	98.17 218	92.61 240	98.62 136	99.57 129	91.87 166	99.67 166	98.87 98	99.99 21	99.99 24
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS		94.82 234	94.74 231	95.06 300	98.00 218	89.19 375	99.08 305	97.55 290	94.10 166	94.71 262	99.62 121	80.51 330	99.74 154	96.04 215	93.06 303	96.25 316

XVG-ACMP-BASELINE		91.22 335	90.75 326	92.63 382	93.73 392	85.61 411	98.52 371	97.44 302	92.77 230	89.90 324	96.85 322	66.64 423	98.39 276	92.29 291	88.61 327	93.89 384

casdiffmvs_mvg		96.43 174	95.94 181	97.89 175	97.44 266	95.47 201	99.86 140	97.29 327	93.35 199	96.03 236	99.19 173	85.39 271	98.72 243	97.89 160	97.04 221	99.49 177
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		92.96 295	92.71 290	93.71 355	95.43 363	88.67 385	99.75 182	97.62 281	92.81 226	90.05 318	98.49 259	75.24 380	98.40 274	95.84 219	89.12 318	94.07 368

LGP-MVS_train				93.71 355	95.43 363	88.67 385		97.62 281	92.81 226	90.05 318	98.49 259	75.24 380	98.40 274	95.84 219	89.12 318	94.07 368

baseline		96.43 174	95.98 173	97.76 187	97.34 277	95.17 224	99.51 249	97.17 344	93.92 178	96.90 207	99.28 157	85.37 272	98.64 255	97.50 174	96.86 230	99.46 180

test11								98.44 147

door								90.31 468

EPNet_dtu		95.71 208	95.39 203	96.66 249	98.92 144	93.41 280	99.57 237	98.90 50	96.19 93	97.52 183	98.56 253	92.65 143	97.36 333	77.89 432	98.33 173	99.20 227
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x2688		96.81 151	96.53 150	97.64 194	98.91 148	93.07 286	99.65 216	99.80 3	95.64 108	95.39 254	98.86 221	84.35 290	99.90 111	96.98 192	99.16 143	99.95 82

EPNet		98.49 45	98.40 39	98.77 104	99.62 90	96.80 143	99.90 113	99.51 16	97.60 33	99.20 98	99.36 150	93.71 112	99.91 109	97.99 153	98.71 163	99.61 146
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS						91.85 318

HQP-NCC					95.78 344		99.87 129		96.82 63	93.37 281

ACMP_Plane					95.78 344		99.87 129		96.82 63	93.37 281

APD-MVS		98.62 36	98.35 46	99.41 43	99.90 46	98.51 63	99.87 129	98.36 187	94.08 167	99.74 42	99.73 90	94.08 100	99.74 154	99.42 66	99.99 21	99.99 24
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS														97.92 157

HQP4-MVS										93.37 281			98.39 276			94.53 324

HQP3-MVS								97.89 251							89.60 311

HQP2-MVS												80.65 328

CNVR-MVS		99.40 1	99.26 1	99.84 6	99.98 2	99.51 6	99.98 20	98.69 81	98.20 9	99.93 2	99.98 2	96.82 26	100.00 1	99.75 40	100.00 1	99.99 24

NCCC		99.37 2	99.25 2	99.71 16	99.96 8	99.15 23	99.97 38	98.62 97	98.02 21	99.90 6	99.95 3	97.33 19	100.00 1	99.54 57	100.00 1	100.00 1

114514_t		97.41 121	96.83 135	99.14 72	99.51 100	97.83 93	99.89 123	98.27 205	88.48 362	99.06 111	99.66 114	90.30 194	99.64 171	96.32 211	99.97 42	99.96 74

CP-MVS		98.45 48	98.32 47	98.87 97	99.96 8	96.62 150	99.97 38	98.39 179	94.43 149	98.90 118	99.87 31	94.30 92	100.00 1	99.04 83	99.99 21	99.99 24

DSMNet-mixed		88.28 382	88.24 376	88.42 426	89.64 447	75.38 455	98.06 395	89.86 470	85.59 402	88.20 367	92.14 437	76.15 374	91.95 455	78.46 430	96.05 245	97.92 289

tpm2		95.47 216	95.18 212	96.35 261	96.91 307	91.70 326	96.96 420	97.93 246	88.04 369	98.44 146	95.40 374	93.32 121	97.97 310	94.00 258	95.61 265	99.38 194

NP-MVS					95.77 347	91.79 320					98.65 240

EG-PatchMatch MVS		85.35 398	83.81 401	89.99 414	90.39 441	81.89 438	98.21 390	96.09 418	81.78 431	74.73 451	93.72 422	51.56 458	97.12 352	79.16 427	88.61 327	90.96 436

tpm cat1		93.51 283	92.52 298	96.47 253	97.77 233	91.47 336	96.13 435	98.06 233	80.98 435	92.91 289	93.78 420	89.66 200	98.87 223	87.03 372	96.39 238	99.09 237

SteuartSystems-ACMMP		99.02 16	98.97 14	99.18 62	98.72 161	97.71 98	99.98 20	98.44 147	96.85 61	99.80 25	99.91 18	97.57 8	99.85 128	99.44 65	99.99 21	99.99 24
Skip Steuart: Steuart Systems R&D Blog.
CostFormer		96.10 191	95.88 185	96.78 244	97.03 296	92.55 303	97.08 417	97.83 259	90.04 332	98.72 131	94.89 400	95.01 65	98.29 289	96.54 207	95.77 255	99.50 175

CR-MVSNet		93.45 286	92.62 291	95.94 271	96.29 330	92.66 299	92.01 458	96.23 414	92.62 239	96.94 205	93.31 426	91.04 178	96.03 410	79.23 424	95.96 248	99.13 233

JIA-IIPM		91.76 326	90.70 327	94.94 304	96.11 335	87.51 398	93.16 454	98.13 228	75.79 449	97.58 182	77.68 467	92.84 137	97.97 310	88.47 353	96.54 232	99.33 205

Patchmtry		89.70 368	88.49 372	93.33 365	96.24 333	89.94 369	91.37 461	96.23 414	78.22 443	87.69 372	93.31 426	91.04 178	96.03 410	80.18 422	82.10 383	94.02 371

PatchT		90.38 352	88.75 368	95.25 296	95.99 339	90.16 361	91.22 462	97.54 292	76.80 445	97.26 194	86.01 461	91.88 165	96.07 409	66.16 459	95.91 252	99.51 173

tpmrst		96.27 187	95.98 173	97.13 230	97.96 221	93.15 285	96.34 431	98.17 218	92.07 265	98.71 132	95.12 390	93.91 105	98.73 241	94.91 238	96.62 231	99.50 175

BH-w/o		95.71 208	95.38 204	96.68 248	98.49 184	92.28 308	99.84 148	97.50 298	92.12 264	92.06 300	98.79 228	84.69 284	98.67 251	95.29 227	99.66 95	99.09 237

tpm		93.70 279	93.41 271	94.58 319	95.36 365	87.41 399	97.01 418	96.90 387	90.85 306	96.72 213	94.14 417	90.40 192	96.84 373	90.75 322	88.54 330	99.51 173

DELS-MVS		98.54 41	98.22 52	99.50 34	99.15 121	98.65 57	100.00 1	98.58 104	97.70 31	98.21 161	99.24 167	92.58 147	99.94 92	98.63 115	99.94 59	99.92 92
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		95.18 225	94.83 225	96.22 264	98.36 192	91.22 338	99.80 164	97.32 322	90.91 304	91.08 307	98.67 237	83.51 295	98.54 262	94.23 256	99.61 103	98.92 253

RPMNet		89.76 367	87.28 384	97.19 229	96.29 330	92.66 299	92.01 458	98.31 198	70.19 460	96.94 205	85.87 462	87.25 238	99.78 145	62.69 464	95.96 248	99.13 233

MVSTER		95.53 215	95.22 210	96.45 256	98.56 172	97.72 97	99.91 107	97.67 273	92.38 254	91.39 304	97.14 308	97.24 20	97.30 340	94.80 241	87.85 338	94.34 342

CPTT-MVS		97.64 109	97.32 113	98.58 121	99.97 3	95.77 187	99.96 52	98.35 189	89.90 334	98.36 152	99.79 62	91.18 176	99.99 39	98.37 129	99.99 21	99.99 24

GBi-Net		90.88 340	89.82 346	94.08 340	97.53 260	91.97 313	98.43 375	96.95 380	87.05 381	89.68 329	94.72 402	71.34 402	96.11 405	87.01 373	85.65 354	94.17 354

PVSNet_Blended_VisFu		97.27 126	96.81 137	98.66 112	98.81 155	96.67 148	99.92 99	98.64 90	94.51 142	96.38 227	98.49 259	89.05 212	99.88 122	97.10 187	98.34 172	99.43 189

PVSNet_BlendedMVS		96.05 193	95.82 187	96.72 247	99.59 91	96.99 134	99.95 71	99.10 34	94.06 170	98.27 156	95.80 353	89.00 214	99.95 84	99.12 77	87.53 345	93.24 407

UnsupCasMVSNet_eth		85.52 395	83.99 397	90.10 412	89.36 448	83.51 427	96.65 426	97.99 239	89.14 341	75.89 449	93.83 419	63.25 436	93.92 439	81.92 411	67.90 454	92.88 415

UnsupCasMVSNet_bld		79.97 425	77.03 430	88.78 422	85.62 456	81.98 437	93.66 450	97.35 313	75.51 451	70.79 457	83.05 464	48.70 461	94.91 430	78.31 431	60.29 467	89.46 453

PVSNet_Blended		97.94 81	97.64 95	98.83 99	99.59 91	96.99 134	100.00 1	99.10 34	95.38 115	98.27 156	99.08 182	89.00 214	99.95 84	99.12 77	99.25 139	99.57 157

FMVSNet5		88.32 381	87.47 383	90.88 398	96.90 310	88.39 391	97.28 411	95.68 427	82.60 428	84.67 407	92.40 435	79.83 337	91.16 457	76.39 439	81.51 388	93.09 410

test1		90.88 340	89.82 346	94.08 340	97.53 260	91.97 313	98.43 375	96.95 380	87.05 381	89.68 329	94.72 402	71.34 402	96.11 405	87.01 373	85.65 354	94.17 354

new_pmnet		84.49 407	82.92 407	89.21 418	90.03 444	82.60 432	96.89 422	95.62 429	80.59 436	75.77 450	89.17 448	65.04 430	94.79 432	72.12 448	81.02 396	90.23 442

FMVSNet3		92.69 303	91.58 313	95.99 268	98.29 197	97.42 114	99.26 290	97.62 281	89.80 336	89.68 329	95.32 380	81.62 315	96.27 399	87.01 373	85.65 354	94.29 344

dp		95.05 228	94.43 235	96.91 238	97.99 219	92.73 297	96.29 433	97.98 241	89.70 337	95.93 239	94.67 406	93.83 110	98.45 268	86.91 376	96.53 233	99.54 163

FMVSNet2		91.02 337	89.56 351	95.41 290	97.53 260	95.74 189	98.98 322	97.41 307	87.05 381	88.43 363	95.00 396	71.34 402	96.24 401	85.12 388	85.21 359	94.25 347

FMVSNet1		88.50 380	86.64 387	94.08 340	95.62 361	91.97 313	98.43 375	96.95 380	83.00 424	86.08 397	94.72 402	59.09 447	96.11 405	81.82 412	84.07 370	94.17 354

N_pmnet		80.06 423	80.78 419	77.89 443	91.94 426	45.28 481	98.80 350	56.82 483	78.10 444	80.08 431	93.33 424	77.03 359	95.76 416	68.14 455	82.81 376	92.64 418

cascas		94.64 245	93.61 259	97.74 189	97.82 230	96.26 166	99.96 52	97.78 263	85.76 398	94.00 276	97.54 298	76.95 362	99.21 196	97.23 183	95.43 269	97.76 296

BH-RMVSNet		95.18 225	94.31 240	97.80 179	98.17 208	95.23 220	99.76 178	97.53 294	92.52 247	94.27 273	99.25 166	76.84 363	98.80 231	90.89 319	99.54 110	99.35 202

UGNet		95.33 221	94.57 233	97.62 198	98.55 175	94.85 231	98.67 361	99.32 26	95.75 105	96.80 211	96.27 340	72.18 398	99.96 75	94.58 248	99.05 150	98.04 287
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		98.10 76	97.60 97	99.60 23	98.92 144	99.28 17	99.89 123	99.52 14	95.58 110	98.24 160	99.39 147	93.33 120	99.74 154	97.98 155	95.58 266	99.78 114

XXY-MVS		91.82 319	90.46 331	95.88 273	93.91 389	95.40 207	98.87 341	97.69 272	88.63 360	87.87 370	97.08 311	74.38 389	97.89 316	91.66 304	84.07 370	94.35 340

EC-MVSNet		97.38 123	97.24 116	97.80 179	97.41 268	95.64 196	99.99 5	97.06 367	94.59 139	99.63 56	99.32 152	89.20 211	98.14 300	98.76 105	99.23 141	99.62 142

sss		97.57 112	97.03 126	99.18 62	98.37 191	98.04 82	99.73 192	99.38 22	93.46 195	98.76 129	99.06 186	91.21 172	99.89 116	96.33 210	97.01 225	99.62 142

Test_1112_low_res		95.72 206	94.83 225	98.42 140	97.79 232	96.41 159	99.65 216	96.65 403	92.70 234	92.86 291	96.13 346	92.15 160	99.30 191	91.88 302	93.64 295	99.55 159

1112_ss		96.01 195	95.20 211	98.42 140	97.80 231	96.41 159	99.65 216	96.66 402	92.71 233	92.88 290	99.40 145	92.16 159	99.30 191	91.92 301	93.66 294	99.55 159

ab-mvs-re		8.28 447	11.04 450	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	99.40 145	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

ab-mvs		94.69 242	93.42 269	98.51 132	98.07 215	96.26 166	96.49 428	98.68 83	90.31 326	94.54 263	97.00 316	76.30 371	99.71 158	95.98 216	93.38 299	99.56 158

TR-MVS		94.54 247	93.56 264	97.49 212	97.96 221	94.34 253	98.71 356	97.51 297	90.30 327	94.51 265	98.69 236	75.56 377	98.77 235	92.82 287	95.99 246	99.35 202

MDTV_nov1_ep13_2view						96.26 166	96.11 436		91.89 271	98.06 165		94.40 84		94.30 254		99.67 129

MDTV_nov1_ep13			95.69 192		97.90 224	94.15 258	95.98 439	98.44 147	93.12 212	97.98 167	95.74 355	95.10 60	98.58 258	90.02 334	96.92 227

MIMVSNet1		82.58 415	80.51 420	88.78 422	86.68 454	84.20 421	96.65 426	95.41 434	78.75 442	78.59 438	92.44 432	51.88 457	89.76 461	65.26 461	78.95 409	92.38 424

MIMVSNet		90.30 355	88.67 369	95.17 298	96.45 329	91.64 328	92.39 456	97.15 347	85.99 395	90.50 315	93.19 428	66.95 421	94.86 431	82.01 410	93.43 297	99.01 246

IterMVS-LS		92.69 303	92.11 303	94.43 330	96.80 315	92.74 295	99.45 262	96.89 388	88.98 347	89.65 332	95.38 377	88.77 217	96.34 396	90.98 316	82.04 384	94.22 350
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet		96.34 181	96.07 167	97.13 230	97.37 274	94.96 228	99.53 246	97.91 250	91.55 282	95.37 255	98.32 271	95.05 63	97.13 350	93.80 268	95.75 257	99.30 214
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref															87.04 347

IterMVS		90.91 339	90.17 341	93.12 371	96.78 319	90.42 357	98.89 336	97.05 370	89.03 344	86.49 390	95.42 373	76.59 367	95.02 426	87.22 368	84.09 369	93.93 381
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon		98.41 53	98.02 68	99.56 29	99.97 3	98.70 52	99.92 99	98.44 147	92.06 267	98.40 151	99.84 48	95.68 47	100.00 1	98.19 140	99.71 92	99.97 66

MVS_111021_LR		98.42 52	98.38 41	98.53 129	99.39 105	95.79 186	99.87 129	99.86 2	96.70 69	98.78 124	99.79 62	92.03 163	99.90 111	99.17 76	99.86 79	99.88 97

DP-MVS		94.54 247	93.42 269	97.91 173	99.46 104	94.04 261	98.93 332	97.48 300	81.15 434	90.04 320	99.55 130	87.02 242	99.95 84	88.97 345	98.11 184	99.73 119

ACMMP++															88.23 334

HQP-MVS		94.61 246	94.50 234	94.92 305	95.78 344	91.85 318	99.87 129	97.89 251	96.82 63	93.37 281	98.65 240	80.65 328	98.39 276	97.92 157	89.60 311	94.53 324

QAPM		95.40 218	94.17 243	99.10 78	96.92 306	97.71 98	99.40 265	98.68 83	89.31 340	88.94 352	98.89 211	82.48 304	99.96 75	93.12 284	99.83 81	99.62 142

Vis-MVSNet		95.72 206	95.15 214	97.45 213	97.62 252	94.28 254	99.28 287	98.24 209	94.27 162	96.84 209	98.94 207	79.39 340	98.76 237	93.25 278	98.49 169	99.30 214
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet		86.22 392	83.19 405	95.31 294	96.71 322	90.29 358	92.12 457	97.33 317	62.85 464	86.82 384	70.37 469	69.37 410	97.49 330	75.12 442	97.99 189	98.15 283

IS-MVSNet		96.29 185	95.90 184	97.45 213	98.13 212	94.80 234	99.08 305	97.61 284	92.02 269	95.54 252	98.96 200	90.64 187	98.08 304	93.73 272	97.41 202	99.47 178

HyFIR lowres test		96.66 163	96.43 155	97.36 223	99.05 127	93.91 266	99.70 206	99.80 3	90.54 318	96.26 229	98.08 281	92.15 160	98.23 296	96.84 199	95.46 267	99.93 87

EPMVS		96.53 170	96.01 170	98.09 160	98.43 187	96.12 178	96.36 430	99.43 20	93.53 192	97.64 181	95.04 393	94.41 83	98.38 280	91.13 311	98.11 184	99.75 117

PAPM_NR		98.12 75	97.93 78	98.70 108	99.94 16	96.13 176	99.82 158	98.43 155	94.56 140	97.52 183	99.70 99	94.40 84	99.98 50	97.00 190	99.98 32	99.99 24

TAMVS		95.85 201	95.58 196	96.65 250	97.07 294	93.50 277	99.17 297	97.82 260	91.39 292	95.02 260	98.01 283	92.20 158	97.30 340	93.75 271	95.83 254	99.14 232

PAPR		98.52 43	98.16 58	99.58 28	99.97 3	98.77 46	99.95 71	98.43 155	95.35 116	98.03 166	99.75 79	94.03 102	99.98 50	98.11 145	99.83 81	99.99 24

RPSCF		91.80 323	92.79 288	88.83 421	98.15 210	69.87 460	98.11 393	96.60 405	83.93 416	94.33 271	99.27 160	79.60 339	99.46 187	91.99 299	93.16 301	97.18 309

Vis-MVSNet (Re-imp)		96.32 182	95.98 173	97.35 225	97.93 223	94.82 233	99.47 257	98.15 226	91.83 274	95.09 259	99.11 180	91.37 171	97.47 331	93.47 276	97.43 199	99.74 118

test_0402		85.58 394	83.94 399	90.50 406	93.81 391	85.04 415	98.55 367	95.20 439	76.01 447	79.72 434	95.13 389	64.15 433	96.26 400	66.04 460	86.88 348	90.21 443

MVS_111021_HR		98.72 31	98.62 29	99.01 88	99.36 107	97.18 123	99.93 96	99.90 1	96.81 66	98.67 133	99.77 69	93.92 104	99.89 116	99.27 72	99.94 59	99.96 74

CSCG		97.10 135	97.04 125	97.27 228	99.89 49	91.92 317	99.90 113	99.07 37	88.67 358	95.26 258	99.82 53	93.17 129	99.98 50	98.15 143	99.47 123	99.90 95

PatchMatch-RL		96.04 194	95.40 202	97.95 167	99.59 91	95.22 221	99.52 247	99.07 37	93.96 175	96.49 222	98.35 268	82.28 305	99.82 140	90.15 333	99.22 142	98.81 260

API-MVS		97.86 87	97.66 93	98.47 134	99.52 98	95.41 206	99.47 257	98.87 58	91.68 279	98.84 120	99.85 37	92.34 156	99.99 39	98.44 125	99.96 46	100.00 1

Test By Simon												92.82 139

TDRefinement		84.76 403	82.56 410	91.38 396	74.58 473	84.80 419	97.36 410	94.56 449	84.73 411	80.21 430	96.12 348	63.56 434	98.39 276	87.92 359	63.97 461	90.95 437

USDC		90.00 363	88.96 364	93.10 373	94.81 372	88.16 393	98.71 356	95.54 431	93.66 189	83.75 413	97.20 307	65.58 426	98.31 287	83.96 397	87.49 346	92.85 416

EPP-MVSNet		96.69 161	96.60 147	96.96 237	97.74 235	93.05 288	99.37 273	98.56 112	88.75 356	95.83 243	99.01 191	96.01 39	98.56 260	96.92 196	97.20 211	99.25 222

PMMVS		96.76 155	96.76 139	96.76 245	98.28 199	92.10 312	99.91 107	97.98 241	94.12 165	99.53 71	99.39 147	86.93 244	98.73 241	96.95 195	97.73 192	99.45 185

PAPM		98.60 37	98.42 38	99.14 72	96.05 337	98.96 27	99.90 113	99.35 24	96.68 70	98.35 153	99.66 114	96.45 35	98.51 263	99.45 64	99.89 74	99.96 74

ACMMP		97.74 102	97.44 106	98.66 112	99.92 35	96.13 176	99.18 296	99.45 18	94.84 130	96.41 226	99.71 96	91.40 170	99.99 39	97.99 153	98.03 188	99.87 99
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		97.76 100	97.38 109	98.92 96	99.53 97	96.84 139	99.87 129	98.14 227	93.78 184	96.55 220	99.69 103	92.28 157	99.98 50	97.13 185	99.44 127	99.93 87

PatchmatchNet		95.94 197	95.45 199	97.39 220	97.83 229	94.41 248	96.05 437	98.40 176	92.86 223	97.09 198	95.28 385	94.21 97	98.07 306	89.26 343	98.11 184	99.70 124
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS		98.41 53	98.21 53	99.03 84	99.86 57	97.10 130	99.98 20	98.80 71	90.78 314	99.62 59	99.78 66	95.30 56	100.00 1	99.80 31	99.93 65	99.99 24

F-COLMAP		96.93 147	96.95 128	96.87 241	99.71 82	91.74 322	99.85 143	97.95 244	93.11 213	95.72 247	99.16 178	92.35 155	99.94 92	95.32 226	99.35 135	98.92 253

ANet_high		56.10 438	52.24 441	67.66 455	49.27 481	56.82 471	83.94 469	82.02 478	70.47 459	33.28 478	64.54 473	17.23 479	69.16 476	45.59 473	23.85 475	77.02 468

wuyk23d		20.37 446	20.84 449	18.99 462	65.34 478	27.73 485	50.43 474	7.67 486	9.50 479	8.01 480	6.34 480	6.13 483	26.24 479	23.40 480	10.69 478	2.99 477

OMC-MVS		97.28 125	97.23 117	97.41 218	99.76 72	93.36 284	99.65 216	97.95 244	96.03 96	97.41 188	99.70 99	89.61 202	99.51 176	96.73 202	98.25 178	99.38 194

MG-MVS		98.91 22	98.65 27	99.68 17	99.94 16	99.07 25	99.64 220	99.44 19	97.33 43	99.00 114	99.72 93	94.03 102	99.98 50	98.73 107	100.00 1	100.00 1

AdaColmap		97.23 129	96.80 138	98.51 132	99.99 1	95.60 198	99.09 303	98.84 65	93.32 201	96.74 212	99.72 93	86.04 257	100.00 1	98.01 151	99.43 128	99.94 86

uanet		0.00 449	0.00 452	0.00 463	0.00 486	0.00 488	0.00 475	0.00 487	0.00 481	0.00 482	0.00 482	0.00 485	0.00 482	0.00 481	0.00 480	0.00 478

ITE_SJBPF				92.38 383	95.69 357	85.14 414		95.71 426	92.81 226	89.33 342	98.11 280	70.23 408	98.42 270	85.91 383	88.16 335	93.59 399

DeepMVS_CX				82.92 439	95.98 341	58.66 470		96.01 419	92.72 232	78.34 439	95.51 368	58.29 448	98.08 304	82.57 405	85.29 357	92.03 427

TinyColmap		87.87 387	86.51 388	91.94 389	95.05 369	85.57 412	97.65 405	94.08 452	84.40 414	81.82 421	96.85 322	62.14 440	98.33 285	80.25 421	86.37 351	91.91 429

MAR-MVS		97.43 116	97.19 119	98.15 156	99.47 102	94.79 235	99.05 314	98.76 73	92.65 238	98.66 134	99.82 53	88.52 220	99.98 50	98.12 144	99.63 98	99.67 129
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		89.25 376	88.85 365	90.45 408	92.81 414	81.19 443	98.12 392	94.79 444	91.44 287	86.29 394	97.11 309	65.30 429	98.11 302	88.53 351	85.25 358	92.07 425

MSDG		94.37 257	93.36 276	97.40 219	98.88 151	93.95 265	99.37 273	97.38 309	85.75 400	90.80 313	99.17 175	84.11 293	99.88 122	86.35 377	98.43 171	98.36 279

LS3D		95.84 202	95.11 215	98.02 165	99.85 60	95.10 226	98.74 353	98.50 136	87.22 380	93.66 279	99.86 33	87.45 234	99.95 84	90.94 317	99.81 87	99.02 245

CLD-MVS		94.06 267	93.90 253	94.55 321	96.02 338	90.69 348	99.98 20	97.72 269	96.62 74	91.05 309	98.85 224	77.21 355	98.47 264	98.11 145	89.51 316	94.48 328
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS		68.72 431	68.72 432	68.71 454	65.95 477	44.27 483	95.97 440	94.74 445	51.13 469	53.26 471	90.50 444	25.11 473	83.00 470	60.80 465	80.97 398	78.87 467

Gipuma		66.95 436	65.00 436	72.79 449	91.52 432	67.96 461	66.16 473	95.15 441	47.89 470	58.54 467	67.99 472	29.74 468	87.54 466	50.20 471	77.83 417	62.87 472
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015

High-resolution multi-view benchmark