Back to Datasets
muses
DEPTHModel: UniDepthV2
Split: full
Variant:
_UniDepthV2_clearFiles: 333
Metrics: 13
Compare with:
absrel / median
0.2079
absrel / p90
0.7159
absrel / median
0.2078
absrel / p90
0.7153
rmse / median
2.5993
rmse / p90
13.6742
silog / mean
0.3932
silog / median
0.1963
silog / p90
0.6827
absrel / median
0.1957
absrel / p90
0.7370
rmse / median
8.8964
rmse / p90
34.5740
silog / mean
0.4006
silog / median
0.1953
silog / p90
0.9179
absrel / median
0.2134
absrel / p90
0.7133
rmse / median
3.2747
rmse / p90
13.9495
silog / mean
0.3969
silog / median
0.2023
silog / p90
0.6974
absrel / median
0.2007
absrel / p90
0.7110
rmse / median
1.5020
rmse / p90
5.1775
silog / mean
0.2360
silog / median
0.1875
silog / p90
0.5790
rmse / median
2.6111
rmse / p90
13.9371
silog / mean
0.3944
silog / median
0.1965
silog / p90
0.6849
image mean / absrel
0.5296
all / absrel
0.5302
all / delta1
0.5627
all / delta2
0.8124
all / delta3
0.8953
all / log10
0.1360
all / mae
7.7269
all / rmse
19.2235
all / rmse log
0.4575
all / silog
0.3932
all / sqrel
41.7170
image mean / delta1
0.5625
image mean / delta2
0.8120
image mean / delta3
0.8950
far / absrel
0.4772
far / delta1
0.4534
far / delta2
0.6684
far / delta3
0.7856
far / log10
0.1797
far / mae
20.9131
far / rmse
30.3038
far / rmse log
0.5280
far / silog
0.4006
far / sqrel
34.9495
image mean / log10
0.1361
image mean / mae
7.8036
mid / absrel
0.5175
mid / delta1
0.5373
mid / delta2
0.7951
mid / delta3
0.8864
mid / log10
0.1407
mid / mae
8.7504
mid / rmse
19.9895
mid / rmse log
0.4638
mid / silog
0.3969
mid / sqrel
39.8822
near / absrel
0.5163
near / delta1
0.6237
near / delta2
0.8741
near / delta3
0.9297
near / log10
0.1184
near / mae
3.4778
near / rmse
7.3038
near / rmse log
0.3582
near / silog
0.2360
near / sqrel
35.9318
image mean / rmse
19.3667
image mean / rmse log
0.4580
image mean / silog
0.3944
image mean / sqrel
41.6476
image median / absrel
0.3792
all / absrel
0.3793
all / delta1
0.5904
all / delta2
0.8623
all / delta3
0.9236
all / log10
0.1214
all / mae
6.1554
all / rmse
15.4849
all / rmse log
0.4180
all / silog
0.3590
all / sqrel
11.8802
image median / delta1
0.5904
image median / delta2
0.8621
image median / delta3
0.9233
far / absrel
0.3508
far / delta1
0.4779
far / delta2
0.7523
far / delta3
0.8698
far / log10
0.1515
far / mae
15.0509
far / rmse
21.7449
far / rmse log
0.4807
far / silog
0.3750
far / sqrel
10.6998
image median / log10
0.1216
image median / mae
6.1554
mid / absrel
0.3718
mid / delta1
0.5646
mid / delta2
0.8501
mid / delta3
0.9195
mid / log10
0.1249
mid / mae
6.4837
mid / rmse
15.9247
mid / rmse log
0.4205
mid / silog
0.3594
mid / sqrel
11.6395
near / absrel
0.2588
near / delta1
0.7143
near / delta2
0.9658
near / delta3
0.9923
near / log10
0.0936
near / mae
1.9276
near / rmse
2.8434
near / rmse log
0.2643
near / silog
0.1744
near / sqrel
1.0874
image median / rmse
15.4895
image median / rmse log
0.4194
image median / silog
0.3602
image median / sqrel
12.4253
pixel pool / absrel
0.5081
all / absrel
0.5085
all / delta1
0.5614
all / delta2
0.8164
all / delta3
0.8971
all / log10
0.1347
all / mae
7.4955
all / rmse
23.3813
all / rmse log
0.4945
all / silog
0.4686
all / sqrel
37.0565
pixel pool / delta1
0.5610
pixel pool / delta2
0.8158
pixel pool / delta3
0.8967
far / absrel
0.4032
far / delta1
0.5408
far / delta2
0.7434
far / delta3
0.8370
far / log10
0.1551
far / mae
18.6244
far / rmse
39.8964
far / rmse log
0.5490
far / silog
0.5465
far / sqrel
34.1678
pixel pool / log10
0.1350
pixel pool / mae
7.6098
mid / absrel
0.4672
mid / delta1
0.5431
mid / delta2
0.8049
mid / delta3
0.8935
mid / log10
0.1357
mid / mae
8.0817
mid / rmse
23.8465
mid / rmse log
0.4843
mid / silog
0.4628
mid / sqrel
31.3399
near / absrel
0.6213
near / delta1
0.6061
near / delta2
0.8566
near / delta3
0.9173
near / log10
0.1284
near / mae
3.9484
near / rmse
16.9352
near / rmse log
0.5053
near / silog
0.4473
near / sqrel
50.2906
pixel pool / rmse
23.6054
pixel pool / rmse log
0.4954
pixel pool / silog
0.4701
pixel pool / sqrel
37.0462