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Classification Results: VOC2012 BETA Competition "comp1" (train on VOC2012 data)
This leaderboard shows only those submissions that have been marked as public, and so the displayed rankings should not be considered as definitive.
The highest scoring entry in each column is shown in bold.
Clicking on the blue arrow symbol ( ) at the top of a column will order the submissions from high to low wrt performance on that column.
Average Precision (AP %)
mean aero
plane bicycle bird boat bottle bus car cat chair cow dining
table dog horse motor
bike person potted
plant sheep sofa train tv/
monitor submission date
CSAC-Net V1 [?] 89.4 96.4 92.0 94.0 92.2 77.1 90.5 87.3 95.2 84.0 91.3 78.1 94.1 94.6 93.4 95.2 74.9 91.9 84.2 94.3 86.4 09-Feb- 2020 SRN+ [?] 88.8 98.2 89.6 92.9 92.3 69.3 93.0 89.8 95.9 80.2 87.8 81.2 94.1 95.2 94.0 97.0 71.8 90.4 80.3 96.5 87.6 02-Jul-2018 SFA_NET [?] 87.5 95.2 89.7 92.1 90.1 75.0 88.9 84.7 93.8 83.4 90.9 78.3 93.0 93.4 90.3 92.7 72.1 89.8 83.0 92.1 82.3 22-May- 2018 SE [?] 86.5 98.3 86.4 92.7 92.0 67.1 90.9 84.6 95.6 75.9 84.5 82.1 94.3 93.1 92.6 96.1 62.5 88.0 71.9 96.3 85.1 19-Oct- 2016 LIG_DCNN_FEAT_ALL [?] 85.4 98.6 86.0 93.4 92.2 65.4 91.0 83.6 95.5 73.4 82.1 79.6 94.7 92.9 92.1 95.0 59.4 87.4 67.8 96.0 82.7 08-Sep- 2015 S&P_OverFeast_Fast_Bayes [?] 82.8 97.1 82.3 91.2 89.4 61.2 87.8 80.4 94.0 70.7 77.9 75.7 92.5 89.1 89.6 95.0 56.0 83.2 67.4 93.9 82.1 20-Nov- 2014 VGG16_Imagenet [?] 82.4 95.8 85.2 90.1 86.9 58.9 88.7 84.3 92.2 71.4 76.7 71.3 90.2 87.9 89.6 95.1 59.9 78.7 69.3 92.8 83.0 25-Jul-2020 NUSPSL_CTX_GPM_SCM [?] 82.2 97.3 84.2 80.8 85.3 60.8 89.9 86.8 89.3 75.4 77.8 75.1 83.0 87.5 90.1 95.0 57.8 79.2 73.4 94.5 80.7 30-Oct- 2014 BCE_loss [?] 82.1 97.1 81.7 94.8 85.8 67.8 86.7 83.9 95.4 64.2 82.1 64.8 92.7 88.3 86.7 90.0 55.5 88.2 62.3 92.6 82.3 20-Jan- 2018 Resnet [?] 80.7 98.4 81.1 92.9 88.7 57.1 87.5 73.3 96.7 63.4 90.1 64.0 94.4 95.1 93.0 76.8 43.8 93.0 67.3 93.1 65.2 25-Apr- 2017 CNN_SIGMOID [?] 79.7 96.3 83.0 88.5 84.6 56.5 88.3 82.1 91.9 69.4 68.8 71.3 88.1 83.2 88.6 93.9 50.1 72.6 63.1 93.1 79.6 14-Jun- 2017 NUSPSL_CTX_GPM [?] 78.6 95.5 81.1 79.4 82.5 58.2 87.7 84.1 83.1 68.5 72.8 68.5 76.4 83.3 87.5 92.8 56.5 77.8 67.0 91.2 77.6 13-Oct- 2011 NUS_Context_SVM [?] 78.3 95.3 81.5 78.9 81.8 57.5 87.3 83.7 82.3 68.4 75.0 68.5 75.8 82.9 86.7 92.7 56.8 77.7 66.1 90.7 77.1 05-Oct- 2011 NLPR_PLS_SSVW [?] 78.3 94.5 82.6 79.4 80.7 57.8 87.8 85.5 83.9 66.6 74.2 69.4 75.2 83.0 88.2 93.6 56.2 75.6 64.1 90.0 76.6 13-Oct- 2011 Semi-Semantic Visual Words & Partial Least Squares [?] 78.3 94.5 82.6 79.4 80.7 57.8 87.8 85.5 83.9 66.6 74.2 69.4 75.2 83.0 88.2 93.6 56.2 75.6 64.1 90.0 76.6 13-Oct- 2011 Bayes_Ridge_CNN [?] 77.0 95.0 75.6 87.9 84.1 53.1 83.6 76.1 87.9 66.1 64.8 71.5 86.8 81.1 85.1 93.4 50.9 73.7 56.4 89.7 76.4 18-Nov- 2014 NUSPSL_CTX_GPM_SVM [?] 76.7 94.3 78.5 76.4 80.0 57.0 86.3 82.1 81.5 65.6 74.7 66.5 73.4 81.9 85.4 91.9 53.2 74.0 65.1 89.5 76.1 13-Oct- 2011 Bayes_Ridge_Deep [?] 74.7 93.4 73.5 85.6 80.8 48.9 82.5 73.8 86.3 64.1 62.4 68.7 85.0 78.4 83.1 92.8 48.4 70.7 54.9 87.7 74.0 22-Sep- 2014 CVC_UVA_UNITN [?] 74.3 92.0 74.2 73.0 77.5 54.3 85.2 81.9 76.4 65.2 63.2 68.5 68.9 78.2 81.0 91.6 55.9 69.4 65.4 86.7 77.4 23-Sep- 2012 UvA_UNITN_MostTellingMonkey [?] 73.4 90.1 74.1 66.6 76.0 57.0 85.6 81.2 74.5 63.5 62.7 64.5 66.6 76.5 81.3 90.8 58.7 69.5 66.3 84.7 77.3 13-Oct- 2011 CNNsSVM [?] 72.2 94.6 72.4 86.0 82.8 41.7 82.6 68.8 86.6 53.4 64.6 60.1 82.3 80.5 81.6 87.4 35.4 72.5 49.7 90.1 70.9 27-Jan- 2015 CVC_CLS [?] 71.0 89.3 70.9 69.8 73.9 51.3 84.8 79.6 72.9 63.8 59.4 64.1 64.7 75.5 79.2 91.4 42.7 63.2 61.9 86.7 73.8 23-Sep- 2012 MSRA_USTC_HIGH_ORDER_SVM [?] 70.5 92.8 74.8 69.6 76.1 47.3 83.5 76.4 76.9 59.8 54.5 63.5 67.0 75.1 78.8 90.4 43.2 63.3 60.4 85.6 71.2 13-Oct- 2011 MSRA_USTC_PATCH [?] 70.2 92.7 74.5 69.4 75.4 45.7 83.4 76.5 76.6 59.6 54.5 63.4 67.4 74.8 78.6 90.3 43.0 63.3 58.6 85.2 71.4 12-Oct- 2011 ITI_FK_FUSED_GRAY-RGB-HSV-OP-SIFT [?] 67.1 90.4 65.4 65.8 72.3 37.7 80.6 70.5 72.4 60.3 55.1 61.4 63.6 72.4 77.4 86.8 37.7 61.1 57.2 85.9 68.7 22-Sep- 2012 LIRIS_CLSDET [?] 66.8 90.0 66.2 63.3 70.9 47.0 80.9 73.9 63.9 61.2 52.7 57.9 56.9 69.6 73.9 88.4 46.3 65.5 54.2 81.3 72.8 13-Oct- 2011 ITI_FK_BS_GRAYSIFT [?] 63.2 89.1 62.3 60.0 68.1 33.4 79.8 66.9 70.3 57.4 51.0 55.0 59.3 68.6 74.5 83.1 25.6 57.2 53.8 83.4 64.9 22-Sep- 2012 BPACAD_COMB_LF_AK_WK [?] 61.4 86.5 58.3 59.7 67.4 33.2 74.2 64.0 65.5 58.5 44.8 53.5 57.0 60.7 70.9 84.6 39.4 55.7 50.5 80.7 63.2 13-Oct- 2011 NLPR_IVA_SVM_BOWDect_Convolution [?] 61.1 83.8 69.8 47.8 60.6 45.4 80.5 74.6 60.4 54.0 51.3 45.3 51.5 64.5 72.7 87.7 35.9 57.9 39.8 75.8 62.7 13-Oct- 2011 LIRIS_CLS [?] 61.0 88.3 56.3 59.3 68.6 33.2 76.6 62.2 64.5 55.3 42.6 55.1 56.2 62.0 70.1 82.5 37.3 56.7 48.3 79.6 64.8 13-Oct- 2011 BPACAD_CS_FISH256_LF [?] 60.5 87.1 58.0 60.0 66.5 31.5 75.7 62.1 63.4 57.1 45.4 50.6 55.8 58.4 71.1 84.0 36.6 54.0 50.8 79.3 61.8 13-Oct- 2011 SIFT-LLC-PCAPOOL-DET-SVM [?] 60.4 85.6 66.5 51.9 60.3 45.4 76.9 70.3 65.1 56.4 34.3 49.6 52.5 63.1 71.6 86.8 26.1 57.2 47.9 75.5 65.6 13-Oct- 2011 NLPR_IVA_SVM_BOWDect [?] 60.3 82.9 69.4 45.4 60.1 46.0 80.0 75.1 59.9 54.9 50.7 43.3 50.0 63.4 72.3 88.1 36.1 57.3 37.7 75.2 58.5 13-Oct- 2011 BPACAD_CS_FISH256-1024_SVM_AVGKER [?] 59.8 85.0 57.0 57.7 65.9 30.7 75.0 62.4 64.4 56.9 42.2 50.9 55.3 59.1 69.2 84.2 39.3 52.6 46.7 78.9 61.9 13-Oct- 2011 BPACAD_CS_FISH256-1024_SVM_WEKER [?] 58.2 85.2 55.9 58.6 65.3 33.0 33.8 62.6 65.0 57.9 41.7 51.6 56.0 60.3 69.6 84.2 38.1 55.5 47.9 79.9 62.0 13-Oct- 2011 SIFT-LLC-PCAPOOL-SVM [?] 54.9 83.2 52.5 49.3 59.7 26.0 73.5 58.2 64.4 52.1 36.6 44.9 52.1 57.8 63.8 78.1 19.2 53.1 44.1 72.0 57.4 13-Oct- 2011 JDL_K17_AVG_CLS [?] 54.8 84.2 52.0 54.5 63.2 25.3 71.2 58.0 61.1 50.2 33.3 44.3 49.7 57.9 65.2 79.9 20.9 47.8 43.0 77.7 56.9 13-Oct- 2011 FastScSPM-KDES [?] 45.2 78.1 48.6 38.8 45.7 15.8 70.7 48.5 51.0 43.3 25.3 35.6 38.0 45.5 55.1 68.4 12.9 35.3 29.4 68.4 49.0 13-Oct- 2011 ComplexLogNormal_LogFoveal_PhaseInvariance [?] 36.4 73.2 33.4 31.0 44.7 17.0 57.7 34.4 45.9 41.2 18.1 30.2 34.3 23.1 39.3 57.3 11.9 23.1 25.3 51.2 36.2 23-Sep- 2012 JDL_K17_HOK2_CLS [?] 34.7 83.5 31.1 18.9 46.2 11.7 70.7 26.4 31.7 24.7 8.7 28.7 22.8 34.3 40.4 51.8 8.7 19.2 15.1 63.4 55.0 13-Oct- 2011 DMC-HIK-SVM-SIFT [?] 32.2 55.6 25.5 31.1 36.5 15.8 41.4 40.0 40.6 30.0 17.8 21.1 34.0 27.0 31.1 57.9 11.9 20.8 22.5 48.4 35.7 13-Oct- 2011 nopatch mthod [?] 28.6 65.1 23.9 17.3 36.0 12.6 40.5 31.1 35.4 27.2 10.4 20.8 31.3 13.6 29.9 55.0 10.7 19.2 19.2 42.1 30.9 02-Oct- 2011 max 4 method [?] 25.0 65.1 23.9 12.9 36.0 8.5 33.4 20.5 35.4 21.2 5.8 20.8 31.3 6.9 30.3 55.0 10.7 19.2 10.8 21.7 30.7 02-Oct- 2011 combining methods [?] 19.8 61.5 11.9 12.4 29.7 8.7 30.6 18.4 23.6 21.6 5.8 14.8 18.5 7.1 12.6 47.8 7.2 15.0 9.8 18.8 19.4 02-Oct- 2011
NLPR_KF_SVM [?] 10.6 10.5 9.1 10.7 6.0 6.5 7.2 13.3 12.2 11.5 9.5 5.6 16.7 8.6 6.6 38.9 5.3 15.0 5.0 8.3 5.4 07-Sep-
2011 MAVEN_SCENE_NEW [?] - 81.8 42.1 45.7 55.7 - 70.8 53.6 55.9 43.0 34.6 39.2 44.0 51.4 56.7 64.7 16.5 40.6 37.6 68.8 46.7 11-Oct- 2014
Ensemble of ensemble [?] - - - 88.7 - - - 19-Sep-
2012
Abbreviations
Title Method Affiliation Contributors Description Date
CNN classifier with
BCE loss BCE_loss Shanghai Jiao Tong
University Lutein A VGG-19 architecture and BCE loss is used to train a classifier 2018-01-
20 13:55:13 Linear classifier with Bayes_Ridge_CNN Pohang University of Yong-Deok We trained linear classifier with squared error loss. We use the feature from CNN which is pretrained in imagenet data. 2014-11-
