Multi-label Classification on PASCAL VOC 2007 (test)
97.3mAPQ2L-CvT
Evaluation results
| Method | Links | ||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Q2L-CvTResolution=384x384, Pre-training=ImageNet-22k, Backbone=CvT2021.07 | 97.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Q2L-TResLResolution=448x448, Pre-training=ImageNet-22k, Backbone=TResNetL2021.07 | 96.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| TResNetLResolution=448x448, Pre-training=ImageNet-22k, Backbone=TResNetL2021.07 | 96.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ML-DecoderBackbone=TResNet-L, Input resolution=4482021.11 | 96.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PanCAN2025.12 | 96.4 | 99.8 | 99.5 | 99.3 | 98.9 | 87.5 | 98.8 | 99.2 | 99.4 | 84.7 | 98.6 | 89.2 | 99.3 | 99.4 | 99.6 | 99.8 | 89.9 | 99.5 | 89.3 | 99.5 | 96.7 | — | |
| Q2L-TResLBackbone=TResNetL, Resolution=448x4482021.07 | 96.1 | 99.9 | 98.9 | 99 | 98.4 | 87.7 | 98.6 | 98.8 | 99.1 | 84.5 | 98.3 | 89.2 | 99.2 | 99.2 | 99.2 | 99.3 | 90.2 | 98.8 | 88.3 | 99.5 | 95.5 | — | |
| Q2L2021.11 | 96.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Q2L-TResLbackbone=TResL2025.12 | 96.1 | 99.9 | 98.9 | 99 | 98.4 | 87.7 | 98.6 | 98.8 | 99.1 | 84.5 | 98.3 | 89.2 | 99.2 | 99.2 | 99.2 | 99.3 | 90.2 | 98.8 | 88.3 | 99.5 | 95.5 | — | |
| ADD-GCNResolution=5762021.07 | 96 | 99.8 | 99 | 98.4 | 99 | 86.7 | 98.1 | 98.5 | 98.3 | 85.8 | 98.3 | 88.9 | 98.8 | 99 | 97.4 | 99.2 | 88.3 | 98.7 | 90.7 | 99.5 | 97 | — | |
| ADD-GCN2025.12 | 96 | 99.8 | 99 | 98.4 | 99 | 86.7 | 98.1 | 98.5 | 98.3 | 85.8 | 98.3 | 88.9 | 98.8 | 99 | 97.4 | 99.2 | 88.3 | 98.7 | 90.7 | 99.5 | 97 | — | |
| ASLBackbone=TResNet-L, Pre-training Data=Extra Pretrain Data2020.09 | 95.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ASLBackbone=TResNetL, Resolution=448x4482021.07 | 95.8 | 99.9 | 98.4 | 98.9 | 98.7 | 86.8 | 98.2 | 98.7 | 98.5 | 83.1 | 98.3 | 89.5 | 98.8 | 99.2 | 98.6 | 99.3 | 89.5 | 99.4 | 86.8 | 99.6 | 95.2 | — | |
| ASL2021.11 | 95.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ASL2025.12 | 95.8 | 99.9 | 98.4 | 98.9 | 98.7 | 86.8 | 98.2 | 98.7 | 98.5 | 83.1 | 98.3 | 89.5 | 98.8 | 99.2 | 98.6 | 99.3 | 89.5 | 99.4 | 86.8 | 99.6 | 95.2 | — | |
| ASLBackbone=ResNet101, Pre-training Data=Extra Pretrain Data2020.09 | 95.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SSGRLAggregation=Single Model, Pre-training=COCO2019.08 | 95 | 99.7 | 98.4 | 98 | 97.6 | 85.7 | 96.2 | 98.2 | 98.8 | 82 | 98.1 | 89.7 | 98.8 | 98.7 | 97 | 99 | 86.9 | 98.1 | 85.8 | 99 | 93.7 | — | |
| SSGRLPre-training Data=Extra Pretrain Data2020.09 | 95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BMMLPre-training Data=Extra Pretrain Data2020.09 | 95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SSGRLResolution=5762021.07 | 95 | 99.7 | 98.4 | 98 | 97.6 | 85.7 | 96.2 | 98.2 | 98.8 | 82 | 98.1 | 89.7 | 98.8 | 98.7 | 97 | 99 | 86.9 | 98.1 | 85.8 | 99 | 93.7 | — | |
| SSGRL2021.11 | 95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BMML2021.11 | 95 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MCARResolution=448x4482021.07 | 94.8 | 99.7 | 99 | 98.5 | 98.2 | 85.4 | 96.9 | 97.4 | 98.9 | 83.7 | 95.5 | 88.8 | 99.1 | 98.2 | 95.1 | 99.1 | 84.8 | 97.1 | 87.8 | 98.3 | 94.8 | — | |
| MCAR2025.12 | 94.8 | 99.7 | 99 | 98.5 | 98.2 | 85.4 | 96.9 | 97.4 | 98.9 | 83.7 | 95.5 | 88.8 | 99.1 | 98.2 | 95.1 | 99.1 | 84.8 | 97.1 | 87.8 | 98.3 | 94.8 | — | |
| ASLBackbone=TResNet-L, Pre-training Data=ImageNet Only2020.09 | 94.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ASLBackbone=ResNet101, Pre-training Data=ImageNet Only2020.09 | 94.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ML-GCNPre-training Data=ImageNet Only2020.09 | 94 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ML-GCN2021.11 | 94 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SSGRLAggregation=Single Model, Pre-training=None2019.08 | 93.4 | 99.5 | 97.1 | 97.6 | 97.8 | 82.6 | 94.8 | 96.7 | 98.1 | 78 | 97 | 85.6 | 97.8 | 98.3 | 96.4 | 98.8 | 84.9 | 96.5 | 79.8 | 98.4 | 92.8 | — | |
| SSGRLPre-training Data=ImageNet Only2020.09 | 93.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SSGRL2025.12 | 93.4 | 99.5 | 97.1 | 97.6 | 97.8 | 82.6 | 94.8 | 96.7 | 98.1 | 78 | 97 | 85.6 | 97.8 | 98.3 | 96.4 | 98.1 | 84.9 | 96.5 | 79.8 | 98.4 | 92.8 | — | |
| CD-GTMLL2026.02 | 92.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 79.4 | |
| PF-DLDLBackbone=Net-E, Aggregation Strategy=Max, Fine-tuning Strategy=Proposals2016.11 | 92.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RCPAggregation=Single Model2019.08 | 92.5 | 99.3 | 97.6 | 98 | 96.4 | 79.3 | 93.8 | 96.6 | 97.1 | 78 | 88.7 | 87.1 | 97.1 | 96.3 | 95.4 | 99.1 | 82.1 | 93.6 | 82.2 | 98.4 | 92.8 | — | |
| PF-DLDLBackbone=Net-D, Aggregation Strategy=Max, Fine-tuning Strategy=Proposals2016.11 | 92.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PF-DLDLBackbone=Net-E, Aggregation Strategy=Avg, Fine-tuning Strategy=Proposals2016.11 | 92.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| PF-DLDLBackbone=Net-D, Aggregation Strategy=Avg, Fine-tuning Strategy=Proposals2016.11 | 92.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RARLAggregation=Single Model2019.08 | 92 | 98.6 | 97.1 | 97.1 | 95.5 | 75.6 | 92.8 | 96.8 | 97.3 | 78.3 | 92.2 | 87.6 | 96.9 | 96.5 | 93.6 | 98.5 | 81.6 | 93.1 | 83.2 | 98.5 | 89.3 | — | |
| FeV+LV (fusion)Aggregation=Fusion2019.08 | 92 | 98.2 | 96.9 | 97.1 | 95.8 | 74.3 | 94.2 | 96.7 | 96.7 | 76.7 | 90.5 | 88 | 96.9 | 97.7 | 95.9 | 98.6 | 78.5 | 93.6 | 82.4 | 98.4 | 90.4 | — | |
| FeV+LVPre-training Data=ImageNet Only2020.09 | 92 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RARLResolution=448x4482021.07 | 92 | 98.6 | 97.1 | 97.1 | 95.5 | 75.6 | 92.8 | 96.8 | 97.3 | 78.3 | 92.2 | 87.6 | 96.9 | 96.5 | 93.6 | 98.5 | 81.6 | 93.1 | 83.2 | 98.5 | 89.3 | — | |
| FeV+LV2021.11 | 92 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RARL2025.12 | 92 | 98.6 | 97.1 | 97.1 | 95.5 | 75.6 | 92.8 | 96.8 | 97.3 | 78.3 | 92.2 | 87.6 | 96.9 | 96.5 | 93.6 | 98.5 | 81.6 | 93.1 | 83.2 | 98.5 | 89.3 | — | |
| RDARAggregation=Single Model2019.08 | 91.9 | 98.6 | 97.4 | 96.3 | 96.2 | 75.2 | 92.4 | 96.5 | 97.1 | 76.5 | 92 | 87.7 | 96.8 | 97.5 | 93.8 | 98.5 | 81.6 | 93.7 | 82.8 | 98.6 | 89.3 | — | |
| RNNPre-training Data=ImageNet Only2020.09 | 91.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RDALResolution=448x4482021.07 | 91.9 | 98.6 | 97.4 | 96.3 | 96.2 | 75.2 | 92.4 | 96.5 | 97.1 | 76.5 | 92 | 87.7 | 96.8 | 97.5 | 93.8 | 98.5 | 81.6 | 93.7 | 82.8 | 98.6 | 89.3 | — | |
| RNN2021.11 | 91.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| RDAL2025.12 | 91.9 | 98.6 | 97.4 | 96.3 | 96.2 | 75.2 | 92.4 | 96.5 | 97.1 | 76.5 | 92 | 87.7 | 96.8 | 97.5 | 93.8 | 98.5 | 81.6 | 93.7 | 82.8 | 98.6 | 89.3 | — | |
| ML-Decoder2026.02 | 91.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.6 | |
| MLC-NC2026.02 | 91.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 78.2 | |
| ASL2026.02 | 91.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.5 | |
| BalanceMix2026.02 | 91.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.2 | |
| LCIFS2026.02 | 91.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.8 | |
| LSFA2026.02 | 91.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 77.1 | |
| C-Tran2026.02 | 91.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 76.4 | |
| Full labelTraining Strategy=LinearInit.2022.06 | 91.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DBL2026.02 | 91.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 76.1 | |
| ML-GCN2026.02 | 91 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 76 | |
| HCP-VGGBackbone=Net-D, Aggregation Strategy=Max2016.11 | 90.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| HCPAggregation=Single Model2019.08 | 90.9 | 98.6 | 97.1 | 98 | 95.6 | 75.3 | 94.7 | 95.8 | 97.3 | 73.1 | 94 | 80 | 97.3 | 96.1 | 94.9 | 96.3 | 78.3 | 94.7 | 76.2 | 97.9 | 91.5 | — | |
| HCPResolution=448x4482021.07 | 90.9 | 98.6 | 97.1 | 98 | 95.6 | 75.3 | 94.7 | 95.8 | 97.3 | 73.1 | 90.2 | 80 | 97.3 | 96.1 | 94.9 | 96.3 | 78.3 | 94.7 | 76.2 | 97.9 | 91.5 | — | |
| HCP2025.12 | 90.9 | 98.6 | 97.1 | 98 | 95.6 | 75.3 | 94.7 | 95.8 | 97.3 | 73.1 | 90.2 | 80 | 97.3 | 96.1 | 94.9 | 96.3 | 78.3 | 94.7 | 76.2 | 97.9 | 91.5 | — | |
| SRB2026.02 | 90.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 75.5 | |
| IF-DLDLBackbone=Net-E, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 90.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Fev+Lv-20-VDBackbone=Net-D, Aggregation Strategy=Max, Training Supervision=Ground-truth bounding box information2016.11 | 90.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-DLDLBackbone=Net-E, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 90.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FeV+LVAggregation=Single Model2019.08 | 90.6 | 97.9 | 97 | 96.6 | 94.6 | 73.6 | 93.9 | 96.5 | 95.5 | 73.7 | 90.3 | 82.8 | 95.4 | 97.7 | 95.9 | 98.6 | 77.6 | 88.7 | 78 | 98.3 | 89 | — | |
| Fev+LvResolution=448x4482021.07 | 90.6 | 97.9 | 97 | 96.6 | 94.6 | 73.6 | 93.9 | 96.5 | 95.5 | 73.7 | 90.3 | 82.8 | 95.4 | 97.7 | 95.9 | 98.6 | 77.6 | 88.7 | 78 | 98.3 | 89 | — | |
| Fev+Lv2025.12 | 90.6 | 97.9 | 97 | 96.6 | 94.6 | 73.6 | 93.9 | 96.5 | 95.5 | 73.7 | 90.3 | 82.8 | 95.4 | 97.7 | 95.9 | 98.6 | 77.6 | 88.7 | 78 | 98.3 | 89 | — | |
| PE2026.02 | 90.6 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 75.1 | |
| IF-DLDLBackbone=Net-D, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 90.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-KLBackbone=Net-D, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 90.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-KLBackbone=Net-E, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 90.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-KLBackbone=Net-E, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 90.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Full labelTraining Strategy=End-to-end2022.06 | 90.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-DLDLBackbone=Net-D, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 90.1 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-KLBackbone=Net-D, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 90 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-l2Backbone=Net-D, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 89.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| IF-VGG-l2Backbone=Net-E, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 89.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| CC2026.02 | 89.8 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 73.6 | |
| IF-VGG-l2Backbone=Net-E, Aggregation Strategy=Max, Fine-tuning Strategy=Images2016.11 | 89.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VGG16&19+SVMAggregation=Multiple Models2019.08 | 89.7 | 98.9 | 95 | 96.8 | 95.4 | 69.7 | 90.4 | 93.5 | 96 | 74.2 | 86.6 | 87.8 | 96 | 96.3 | 93.1 | 97.2 | 70 | 92.1 | 80.3 | 98.1 | 87 | — | |
| VGG+SVMResolution=448x4482021.07 | 89.7 | 98.9 | 95 | 96.8 | 95.4 | 69.7 | 90.4 | 93.5 | 96 | 74.2 | 86.6 | 87.8 | 96 | 96.3 | 93.1 | 97.2 | 70 | 92.1 | 80.3 | 98.1 | 87 | — | |
| VGG+SVMclassifier=SVM, backbone=VGG2025.12 | 89.7 | 98.9 | 95 | 96.8 | 95.4 | 69.7 | 90.4 | 93.5 | 96 | 74.2 | 86.6 | 87.8 | 96 | 96.3 | 93.1 | 97.2 | 70 | 92.1 | 80.3 | 98.1 | 87 | — | |
| MLBOTE2026.02 | 89.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 73 | |
| IF-VGG-l2Backbone=Net-D, Aggregation Strategy=Avg, Fine-tuning Strategy=Images2016.11 | 89.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LL-RTraining Strategy=LinearInit.2022.06 | 89.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VGG+SVMBackbone=Net-D, Aggregation Strategy=Max2016.11 | 89.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VGG+SVMBackbone=Net-E, Aggregation Strategy=Max2016.11 | 89.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VGG16+SVMAggregation=Single Model2019.08 | 89.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| VGG19+SVMAggregation=Single Model2019.08 | 89.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LL-CtTraining Strategy=LinearInit.2022.06 | 89.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LL-RTraining Strategy=End-to-end2022.06 | 89.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LL-CtTraining Strategy=End-to-end2022.06 | 89 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| GCB2026.02 | 89 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | 63.1 | |
| RLSDAggregation=Single Model2019.08 | 88.5 | 96.4 | 92.7 | 93.8 | 94.1 | 71.2 | 92.5 | 94.2 | 95.7 | 74.3 | 90 | 74.2 | 95.4 | 96.2 | 92.1 | 97.9 | 66.9 | 93.5 | 73.7 | 97.5 | 87.6 | — | |
| LL-CpTraining Strategy=End-to-end2022.06 | 88.4 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LL-CpTraining Strategy=LinearInit.2022.06 | 88.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| TaI-DPTDPT=true, Zero-shot=true2022.11 | 88.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ROLETraining Strategy=LinearInit.2022.06 | 88.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ROLETraining Strategy=End-to-end2022.06 | 87.9 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — |