Open Images 2019 - Object Detection

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Best sub leaderboard

What if every single team had chosen their best sub for final scoring?
This LB is based on that scenario.

Team name	Public(final)	Private(final)	Private(best)	Public score	Private score	Date
MMfruit ○○○○○	1	1	1	0.6817434985447439	0.6588794353161422	2019-10-01
imagesearch ○○○○○○○	2	2	2	0.6815507331268243	0.6533768152740322	2019-10-01
Prisms ○○○○○○	3	3	3	0.6717006993073649	0.6421400431005828	2019-10-01
PFDet ○○○○○○	4	4	4	0.6545419910916067	0.6222128895998085	2019-10-01
Omni-Detection ○○○	7	5	5	0.6314055993197135	0.6040615299663721	2019-10-01
Schwert ○	8	6	6	0.6279883712167365	0.602313094303076	2019-10-01
Team 5 ○○○○○	6	7	7	0.6321830994466183	0.6021069017689084	2019-10-01
pudae ○	5	8	8	0.6317208574687069	0.5975146316745799	2019-09-29
[ods.ai] n01z3 ○	9	9	9	0.6263424171046708	0.5953512920787639	2019-10-01
dingwoai ○	12	10	10	0.6083479969748391	0.5850483846048451	2019-09-30
J ○○○○○	10	11	11	0.6211436739905456	0.5825979409442268	2019-10-01
Markup Oracles ○○	11	12	12	0.613285678518789	0.5730484091161372	2019-10-01
ang TSS method ○	13	13	13	0.581169428405522	0.5435269016921465	2019-09-30
tito ○	14	14	14	0.5746578634299946	0.5388591260219696	2019-09-26
Appian ○	15	15	15	0.5709064705168942	0.5362945000984799	2019-09-07
Noah ○○○○○	16	16	16	0.5575438473344205	0.5302843645953553	2019-10-01
Wiwide ○	20	17	17	0.5518182548647067	0.521910253123596	2019-09-30
VisualTagging-CVC-UKOBE ○○○○○	18	18	18	0.5525092918917801	0.5218715950147478	2019-10-01
onlyone ○○	25	19	19	0.5426713832311524	0.5195143947673608	2019-08-29
Objectively detecting ○○○○	17	22	20	0.5566244337314427	0.517378572586176	2019-10-01
Wisers ○○	22	21	21	0.5491813284202955	0.5173142441059628	2019-09-30
Quatro ○○○○	21	23	22	0.5494386457507788	0.5143430842783824	2019-09-26
[ods.ai] 512 TPUs ○○	19	24	23	0.5534711236291694	0.5047163938089266	2019-09-30
T Nakamura (2GPUs) ○	24	25	24	0.5426736018005994	0.5038749574624034	2019-10-01